DEV Community: ChatToPDF

Best WhatsApp Transcription Tools: An Honest Guide

ChatToPDF — Fri, 29 May 2026 18:59:53 +0000

This guide compares the best WhatsApp transcription tools by the job you need done — not by abstract accuracy rankings. The best WhatsApp transcription tool depends entirely on the job you are doing. If you need to quickly read one voice note without pressing play, WhatsApp's own built-in transcription is the right answer — it is free, on-device, and instant. If you need to process a standalone audio file, general-purpose transcription apps are a sensible fit. If you need an entire WhatsApp chat exported as a searchable PDF with every voice note transcribed inline, sender names preserved, and timestamps intact, that is what ChatToPDF's Premium+Voice tier ($49 per chat) is built for.

TL;DR: The category that fits you: WhatsApp's built-in transcription for a quick read of one note; a general transcription app for standalone audio files; ChatToPDF for a whole exported chat with voice notes inline in one searchable document. The right tool is the one shaped for your specific job — not the most accurate one in the abstract, and not the cheapest one in isolation. Free options exist at every level; the cost of the dedicated tools reflects batch processing, export format, and sender attribution — not just raw transcription.

How to choose a WhatsApp transcription tool

The single most important question is not "which tool is most accurate" — it is "what is the actual job I am trying to do?" A transcription tool that excels at one job is often irrelevant for another. Here are the criteria that matter, in rough order of importance.

Scope: per-message or whole-chat batch. WhatsApp conversations can run to thousands of messages with dozens of voice notes scattered across the timeline. If you need all of them transcribed in context, a tool that processes one file at a time requires you to manually extract, name, and reassemble each voice note — an approach that is tedious at five voice notes and impractical at fifty. A batch tool processes the entire exported ZIP in one pass and embeds the transcripts in sequence. Know your scope before choosing.

Output format and where you need the result. A transcript that stays inside an app is useful for reading once; a transcript in a PDF, XLSX, or plain-text file is useful for filing, emailing, printing, or submitting to a third party. If the output needs to leave the phone — go to a solicitor, an HR manager, a case-management system, or a personal archive — the format matters as much as the transcription quality.

Sender attribution and timestamp inline. In a multi-participant chat, a voice note transcript without the sender's name and the original timestamp is only half the record. "Someone said this at some point" is not useful for a business archive or a legal document. Look for whether the tool preserves who said what and when — not just what was said.

Language support. Voice notes in WhatsApp come in every language. Most transcription tools support a core set well and degrade for others. If your chat contains voice notes in Arabic, Hindi, Portuguese, or a mixed-language conversation, check language support specifically rather than assuming "it works". WhatsApp publishes the list of languages supported by its built-in transcription on the official WhatsApp FAQ.

Privacy and data handling. Voice notes can contain sensitive personal information. Before uploading to any third-party tool, check their stated data-retention policy. ChatToPDF deletes uploaded files automatically after 7 days; policies at other services vary — check the vendor's current terms.

Price model. Transcription tools charge in very different ways: some are subscription (monthly fee regardless of how much you transcribe), some are per-minute of audio, some are per-conversation. For a one-off archive of a single WhatsApp chat, a per-chat flat fee is often more economical than a recurring subscription you will cancel. For ongoing high-volume use, a per-minute or subscription model may be cheaper. Match the cost model to your usage pattern.

The main options compared

The four categories below cover every practical approach to WhatsApp transcription. I have not invented competitor prices, accuracy percentages, or feature lists — the category rows describe general, verifiable characteristics of each approach. For any specific commercial tool you are evaluating, check its current documentation; features and pricing change.

WhatsApp transcription tool categories — what each option is actually for

Category	Scope	Output / export	Sender + timestamp inline	Languages	Privacy	Best for	Cost model
WhatsApp built-in	One voice note at a time	Transient overlay inside the app — no export	Visible in chat UI but not in the transcript overlay or export	Varies by app version; check your WhatsApp settings	On-device processing — audio stays on your phone	Quickly reading one note without pressing play	Free (built into WhatsApp)
General transcription apps	Usually one audio file at a time; some support batch file upload	Plain text, SRT, or DOCX — typically one transcript per file	Not connected to WhatsApp chat structure; no sender or timestamp	Varies by app; many support major languages well	Varies by vendor — check each app's current retention policy	Transcribing standalone audio or video files	Subscription or per-minute; free tiers usually limited
ChatToPDF (Premium+Voice)	Entire exported WhatsApp chat — all voice notes in one pass	PDF (voice transcripts inline in conversation) + optional XLSX/CSV	Yes — sender name and timestamp preserved with every transcript entry	17 high-accuracy languages; 30+ auto-detected (Deepgram Nova-3)	Files deleted automatically after 7 days; no sharing with third parties	Whole chat as a searchable record — legal, business, archive, accessibility	$49 per chat — one-time flat fee, no subscription
Manual typing / hiring a transcriber	Any audio, any format, any quality	Whatever format the typist produces — Word, PDF, plain text	Only if the typist is given context and instructed to include it	Any language a human speaker understands	Depends on whether a human or a service is involved; review before sharing	Very noisy audio, unusual accents, or where automated tools fail	Time cost if DIY; varies widely if outsourced — check the vendor

The table does not rank these options by quality — they are shaped for different jobs. The right column is not "best"; it is "best for a specific situation."

Convert your WhatsApp chat to PDF

When ChatToPDF is the right choice (and when it isn't)

I want to be honest about this, because a comparison page that pretends one product wins every case is not useful.

ChatToPDF wins when the job is: the whole chat as a document. If you have a WhatsApp conversation — one-to-one or group — that contains a mix of text messages and voice notes, and you need the complete record exported as a searchable document with sender attribution and timestamps, ChatToPDF is the only tool on this list built specifically for that job. The built-in transcription cannot export and does not batch. General transcription apps do not understand the WhatsApp chat structure and cannot attach transcripts to specific senders and moments in the conversation. Manual typing is possible but slow.

The specific situations where I would confidently recommend ChatToPDF's Premium+Voice tier:

Legal and compliance filings — a dispute, an employment matter, a court filing — where you need the voice notes and the surrounding text messages in one timestamped, attributed document
Business records — client approvals, instructions, and agreements given verbally over WhatsApp, where a searchable archive is the difference between "we have a record" and "I think he said this in a voice note somewhere"
Long-term personal archives — family group chats, voice notes from relatives, conversations you want to preserve in a format that does not depend on WhatsApp staying installed
Accessibility situations — making voice note content available to someone who is deaf or hard of hearing, or who cannot play audio in their environment

WhatsApp's built-in transcription wins when the job is: quickly reading one note right now. I mean this genuinely. If someone just sent you a two-minute voice note and you want to skim it on silent in a meeting, tap the note and let WhatsApp transcribe it on-device. Free, instant, no export needed. ChatToPDF is the wrong shape for that job. The WhatsApp speech to text guide covers the built-in feature in detail.

General transcription apps win when the job is: a standalone audio file that has nothing to do with WhatsApp structure. If someone emailed you an MP3 of a meeting recording or a podcast segment, a general-purpose transcription app is the right tool. That app is not going to understand a WhatsApp ZIP file, and ChatToPDF is not going to help you with a non-WhatsApp audio file. Use the right shape.

Manual transcription wins when automated tools fail. Very noisy audio, unusual accents, highly technical vocabulary, low-quality recordings, or languages that are genuinely not well-supported by any automated engine — these are the cases where a human listener still outperforms automated tools. Automated transcription has come a long way, but it is not universal. The transcribe WhatsApp audio guide covers how background noise affects accuracy in detail, including the honest picture of when Deepgram Nova-3 degrades.

What ChatToPDF costs

ChatToPDF uses a per-chat flat fee — one payment, one export, no subscription or recurring charge.

Voice transcription is available on the Premium+Voice tier at $49 per chat. That tier includes: the full PDF with every voice note transcribed inline at its position in the conversation; Deepgram Nova-3 transcription in 17 high-accuracy languages plus 30+ auto-detected; sender name and timestamp preserved with every transcript; XLSX and CSV export alongside the PDF; and up to 8 hours of audio per chat. If you have a chat with dozens of voice notes spread across years, this is the tier that handles it in a single pass.

The Power User tier at $99 per chat adds a priority processing queue and is intended for very large group exports where turnaround time matters.

The other tiers ($7 Basic, $14 Standard, $29 Premium) do not include voice transcription. They produce a chat PDF with text messages and inline media, but voice notes appear as audio-file placeholders rather than readable transcripts.

There is no subscription required. If you have one conversation to export, you pay $49 once. If you have ten, you pay per chat. There is no monthly fee regardless of whether you use the service.

You can upload your ZIP and preview the output — including how many voice notes were detected and what the formatted PDF will look like — before paying anything. The 7-day money-back guarantee means that if the transcription output is not what you needed, you can get a full refund.

Convert your WhatsApp chat to PDF

FAQ

What's the best free option for WhatsApp voice transcription?

WhatsApp's own built-in transcription is the best free option — it is on-device (so your audio never leaves the phone), does not require any third-party app, and works reasonably well for clear recordings in well-supported languages. It transcribes one voice note at a time with no export option. If you need batch transcription or a document you can save and share, the free tier ends there. Some general transcription apps offer limited free tiers — typically a few minutes of audio per month or per day — but features and pricing change, so check each vendor's current offering before relying on it. For a complete WhatsApp chat archive with transcripts, there is no free option that handles sender attribution, timestamps, and batch processing in one step.

Can I transcribe a whole WhatsApp chat at once?

Yes, but not with WhatsApp's built-in feature — that transcribes one voice note at a time and has no export. To batch-transcribe an entire chat, you export the conversation from WhatsApp as a ZIP file (using the "Including Media" option, which includes the voice note audio files), then upload the ZIP to chattopdf.app and select the Premium+Voice tier. ChatToPDF processes all the voice notes in the export in a single pass and returns one PDF with the transcripts embedded inline at their correct positions in the conversation. The WhatsApp voice to text guide walks through this workflow step by step.

Which WhatsApp transcription option is most accurate?

Accuracy depends on audio quality more than tool choice. For clear recordings — indoors, phone near the speaker, minimal background noise — modern automated transcription engines including Deepgram Nova-3 (used by ChatToPDF) perform well across supported languages. For noisy recordings — a busy street, a moving vehicle, wind — accuracy degrades for all automated tools, and a human transcriber may be more reliable. WhatsApp's on-device transcription uses a different underlying model; I cannot benchmark it precisely because the model is not publicly documented. The honest answer is: test with your own audio in your specific language and noise conditions before committing to any approach for something important. ChatToPDF's free upload preview lets you assess quality before paying.

Do any tools keep the sender names and timestamps alongside the transcript?

Among the automated options in this comparison, only ChatToPDF preserves sender names and timestamps as part of the transcript output. WhatsApp's built-in transcription shows the transcript as an overlay on the voice note bubble — you can see the sender's name in context in the chat UI, but it is not part of the transcript text itself and does not appear in any export. General transcription apps process a standalone audio file with no knowledge of who sent it or when — they return a transcript of the spoken content only. For legal, business, or archive use cases where attribution is important, ChatToPDF's approach of embedding the transcript at the exact position in the conversation — with the sender name and timestamp that WhatsApp's own export file records — is the only category that delivers this as part of the output document.

Is my data private when I use a WhatsApp transcription tool?

Privacy practices differ across the categories. WhatsApp's built-in transcription processes audio on your device and audio does not leave the phone — this is the highest-privacy option. General transcription apps typically send audio to cloud servers for processing; data-retention policies vary by vendor, so check each one's current privacy documentation before uploading sensitive conversations. ChatToPDF sends your ZIP to its servers for processing and automatically deletes uploaded files after 7 days. No audio or chat data is shared with third parties. If your voice notes contain sensitive personal or business information — which they often do — review the privacy policy of any service before uploading, regardless of which tool you choose.

Key takeaways

The best WhatsApp transcription tool depends on the job: built-in for one note quickly, general apps for standalone audio files, ChatToPDF for a whole exported chat as a document
WhatsApp's built-in transcription is free, on-device, and private — but transcribes one message at a time with no export capability
General transcription apps handle standalone audio files well but have no knowledge of WhatsApp chat structure, sender names, or timestamps
ChatToPDF Premium+Voice ($49 per chat) batch-processes the entire exported ZIP and embeds transcripts inline in the PDF with sender attribution and timestamps preserved
The transcription engine is Deepgram Nova-3: 17 high-accuracy languages, 30+ auto-detected; accuracy depends mainly on audio quality, not tool choice
No transcription tool performs perfectly on noisy recordings — test with your own audio before committing to anything important
For the whole-chat workflow step by step, see the WhatsApp voice to text guide; for the technical accuracy picture, see the transcribe WhatsApp audio pillar
If your goal is a complete, searchable PDF of the whole conversation — transcripts included — the WhatsApp to PDF guide explains the full process from export ZIP to finished document.

WhatsApp Voice to Text: Turn Voice Notes into Readable Text

ChatToPDF — Fri, 29 May 2026 18:59:37 +0000

The fastest way to do WhatsApp voice to text conversion at scale is to export the entire chat as a ZIP with "Including Media" and process it in one batch. Upload the ZIP file to chattopdf.app and choose the $49 Premium+Voice tier at checkout. Every voice note in the conversation becomes an inline transcript in the PDF — attributed to the sender, placed at the correct timestamp, readable alongside the surrounding text messages.

TL;DR: WhatsApp voice notes can be converted to readable text by exporting your chat as a ZIP (Including Media), uploading it to chattopdf.app, and selecting the $49 Premium+Voice tier. The output is a PDF where every voice note is transcribed inline at its position in the chat, with the sender name and timestamp preserved. Works on both iPhone and Android exports. 17 languages at high accuracy, 30+ more auto-detected. No separate transcription app needed — everything comes out as one searchable document.

How to convert WhatsApp voice notes to text

The entire workflow runs in five steps, from opening WhatsApp to receiving a PDF with every voice note transcribed.

1. Export the chat with Including Media — Open WhatsApp and navigate to the chat that contains the voice notes. On iPhone: tap the contact or group name at the top of the chat → scroll to the bottom of the info screen → tap Export Chat → pick Including Media. On Android: tap the three-dot menu in the top-right corner → More → Export Chat → Include Media. The "Including Media" option is the critical one — it puts the .opus voice note files inside the ZIP alongside the text. Without it, the ZIP contains only the _chat.txt file and there is nothing to transcribe. WhatsApp's official export chat FAQ explains the export sheet in detail.

2. Save the ZIP to your device — After selecting Including Media, WhatsApp generates a ZIP file and opens the share sheet. On iPhone, tap Save to Files and choose a folder (On My iPhone → Downloads is reliable). On Android, share the ZIP to your file manager, Google Drive, or email it to yourself. The ZIP is now a real file on your device, ready to upload.

3. Upload the ZIP to chattopdf.app — Open chattopdf.app in a browser on your phone or desktop. Drag and drop the ZIP onto the upload area, or tap the area to open a file picker and select the ZIP you just saved. The uploader validates the file and shows a preview: total messages, number of voice notes detected, and an estimated output size. This preview is free — no payment yet.

4. Select the Premium+Voice tier ($49 per chat) — The pricing step shows five tiers. Pick Premium+Voice at $49 per chat. This tier enables Deepgram Nova-3 transcription on every voice note in the ZIP. The other tiers ($7, $14, $29) either omit voice notes entirely or include them only as audio-file placeholders rather than transcribed text. The $49 tier is the one that converts voice to readable text. Pay by card — one-time, no subscription, no recurring charge.

5. Download the PDF with inline transcripts — After payment, chattopdf processes the chat and emails the PDF to the address you provided. Typical processing time for a chat with up to a few dozen voice notes is under two minutes. The PDF arrives with every voice note transcribed at its correct position in the conversation — sender name, timestamp, and transcript text all preserved. Open it, search it, print it, or file it.

Convert your WhatsApp chat to PDF

What the output looks like

The key thing about the chattopdf output is that the voice note transcripts are inline in the conversation — not in a separate appendix, not in a separate file, not numbered separately. They appear exactly where the voice notes appeared in the chat, in chronological order, alongside the text messages.

Here is what a section of the resulting PDF looks like with a mixed text-and-voice conversation:

Emma · 09:14

Hey, are you joining the call at 10?

Luca · 09:15 · [voice note — 0:12 — transcript]

"Yeah, I'll be there. Just finishing up the slides. Five more minutes."

Emma · 09:16

Perfect, no rush.

Luca · 09:22 · [voice note — 0:28 — transcript]

"Actually, can we push it to 10:15? I need to send something to the client first and I want to attach the updated version."

Emma · 09:23

Sure, I'll let the others know.

Each transcript line carries the sender name and the timestamp from the original chat. If a voice note is in a language other than English — Spanish, Portuguese, Hindi, Arabic, French, and others — it is transcribed in that language. The transcript text is the spoken content as written text. You can select it, copy it, and search the PDF for keywords that appeared in any voice note.

The voice notes that were sound-only in WhatsApp become readable, searchable, archivable text. The surrounding context — the text messages before and after each voice note — remains intact. The full conversation reads as a single document.

When you would want this

Legal and evidence use cases. If a WhatsApp conversation is relevant to a dispute, a complaint, or a court filing, having the voice notes transcribed as part of the same document that shows the text messages is useful. A judge, solicitor, or HR officer can read the entire exchange — including what was said verbally — without needing to play audio. For more on formatting exported chats for legal purposes, the WhatsApp to PDF guide covers the formal styling options.

Business records and compliance. Sales teams, support teams, and freelancers who conduct substantive conversations over WhatsApp — approvals, agreements, instructions, complaints — often need a readable record of those conversations. Voice notes in a business context frequently contain the actual decision or the actual instruction. Having those as readable text alongside the surrounding messages means the record is complete and searchable, not partially mute.

Personal and family archives. Long family group chats accumulate years of voice notes from relatives — updates, stories, birthday wishes, directions, check-ins. Many of those voice notes are from people whose voices you want to remember. Transcribing them into a PDF creates a readable archive that can be searched, printed, and kept alongside photos and written messages. The voice notes do not stay as audio forever — device storage gets cleared, WhatsApp accounts get deleted, phones change hands. A PDF with the transcripts is a more durable format.

Accessibility. Voice notes are by nature inaccessible to people who are deaf or hard of hearing, or to people who cannot play audio in the environment they are in (commuting, an open-plan office, a meeting). A transcript makes the content of a voice note available regardless of hearing ability or audio environment.

In all of these cases, the value of the chattopdf approach compared to a standalone transcription app is that the transcript lands in context — at the right position in the conversation, attributed to the right speaker, readable alongside the surrounding text. You do not have to manually correlate a list of transcripts against a separate exported chat.

Convert your WhatsApp chat to PDF

Accuracy and languages

The voice transcription uses Deepgram Nova-3, which in my own testing handles clear recordings in supported languages well. In quiet conditions — indoors, phone held near the mouth, no background noise — the transcripts read cleanly with very few errors. In noisy conditions — a moving car, a café, wind — accuracy degrades noticeably and the occasional word or phrase needs a second read. The transcribe WhatsApp audio guide covers the accuracy picture in detail, including how background noise affects results and what the word error rate looks like across recording conditions.

The 17 languages where Deepgram Nova-3 performs at high accuracy include English, Spanish, Portuguese, French, German, Italian, Arabic, Hindi, Indonesian, Turkish, Russian, Dutch, Japanese, Korean, Mandarin, Vietnamese, and Thai. If a voice note is in any of these languages, the transcript is typically clean enough to be useful without editing. For languages beyond this set, the engine falls back to a broader detection model — accuracy varies and some languages may not transcribe usefully. If your chat contains voice notes in a language that is not on that list, I would suggest testing with a single short export before relying on the transcription for anything important.

WhatsApp voice notes are encoded as Opus audio at 16 kHz. That is a narrow frequency range optimised for speech intelligibility, which means the transcription engine receives all the information it needs for speech recognition. The audio format itself is not the limiting factor. The WhatsApp audio format guide explains the Opus codec in more detail if you are curious about the technical side.

For language detection to work correctly, the ZIP must include the voice note files — which is why the "Including Media" export option matters. Without the audio files in the ZIP, there is nothing to transcribe regardless of tier.

Key takeaways

To get WhatsApp voice notes as readable text, export the chat with Including Media — this puts the .opus audio files inside the ZIP, which is required for transcription.
Upload the ZIP to chattopdf.app and choose the $49 Premium+Voice per chat tier. The other tiers do not transcribe voice notes to text.
The output is a PDF where every voice note appears as an inline transcript at its position in the conversation, with sender name and timestamp — not as a separate list or file.
17 languages at high accuracy, 30+ auto-detected. Background noise is the main accuracy factor, not the language or the Opus audio format.
Free alternatives exist (WhatsApp's in-app transcription, Otter.ai, Google Recorder) but require processing voice notes one at a time; ChatToPDF batches the whole chat in a single pass.
Voice calls are not in the chat export and cannot be transcribed. Only voice note messages (the audio clips sent in the chat) are included.
The transcribe WhatsApp audio pillar covers the full technical detail — accuracy by noise level, the Deepgram Nova-3 pipeline, and what the WER looks like across recording conditions.

FAQ

Is there a free way to turn WhatsApp voice notes into text?

Yes — several free options exist. WhatsApp itself has a built-in live transcription feature on some Android versions and iPhones running iOS 17 or later: hold the microphone icon in the voice note player and the app shows a transcript. This works in-app for individual messages and is free. Standalone transcription apps like Otter.ai (limited free tier), Google's Recorder app (Pixel-only, free), and Apple's Voice Memos transcription (US English only, iOS) can also transcribe audio files. The limitation with all of these approaches is that you have to transcribe one voice note at a time, manually, and then correlate the output with the surrounding chat text yourself. ChatToPDF charges $49 for the Premium+Voice tier because it processes the entire chat — potentially dozens of voice notes — in a single batch and delivers the transcripts inline at the correct position in the conversation, attributed to the correct sender, as a single searchable PDF. Whether that is worth it depends on how many voice notes you have and what you need the output for.

Does this work on both iPhone and Android exports?

Yes. The export workflow is slightly different on each platform — on iPhone you reach the Export Chat option via the contact info screen (tap the name at the top of the chat); on Android it is under the three-dot menu → More → Export Chat. Both platforms produce a ZIP file containing a _chat.txt and the voice note .opus files when you export with Including Media. ChatToPDF accepts ZIPs from both platforms and processes them identically. The underlying voice note format is the same on both (Opus codec, .opus extension), so there is no quality or accuracy difference based on which phone the export came from.

What languages are supported for voice note transcription?

17 languages at high accuracy: English, Spanish, Portuguese, French, German, Italian, Arabic, Hindi, Indonesian, Turkish, Russian, Dutch, Japanese, Korean, Mandarin, Vietnamese, and Thai. Beyond these 17, Deepgram Nova-3 auto-detects and attempts transcription for 30+ additional languages, though accuracy varies and some may not produce useful output. Mixed-language voice notes — Hinglish (Hindi + English), code-switching in Arabic dialects, Portuguese–Spanish mixing — are handled in a single pass by Nova-3. The transcript is in the language(s) spoken; there is no translation step. For the full language table with notes on dialect handling, see the transcribe WhatsApp audio pillar.

Do WhatsApp voice calls get transcribed too?

No. WhatsApp voice calls are not recorded or stored in the chat export. The ZIP file that WhatsApp generates contains only messages that appeared in the chat window — voice notes (the short recorded audio clips you send as messages), photos, documents, and the text conversation. A phone call or video call made through WhatsApp does not appear in the chat export because it was a live call, not a stored message. Only voice notes — the microphone icon messages in the conversation — are transcribed.

How long does the transcription take?

For a typical chat with up to a few dozen voice notes, the full process — upload, transcription, PDF generation, email delivery — usually completes in under two minutes after payment. Larger chats with many voice notes or unusually long individual recordings (several minutes each) take longer; in my experience a chat with 50+ voice notes totalling an hour of audio can take five to ten minutes. There is no hard limit on audio duration at the Premium+Voice tier (up to 8 hours of audio per chat). You receive the PDF by email once it is ready, so you do not have to stay on the page.

WhatsApp to PDF Converter Online Free: What Actually Works

ChatToPDF — Fri, 29 May 2026 18:53:45 +0000

Yes, there are genuinely free ways to get a WhatsApp chat into PDF — WhatsApp's built-in export plus your phone's print-to-PDF works at no cost for small chats. But a fully formatted converter that keeps sender names, timestamps, and inline media across a long chat is a paid tool. ChatToPDF's preview is free; conversion starts at $7.

TL;DR: The whatsapp to pdf converter online free options that genuinely exist: WhatsApp's built-in Export Chat + your phone's print-to-PDF (free, works for short chats, breaks on long ones), generic free online tools (typically file-size capped, no media, often watermarked), and ChatToPDF's free preview (see formatting + count + price before paying). A properly formatted conversion — sender attribution, timestamps, inline media, no truncation — starts at $7 on ChatToPDF. No subscription; one-time payment per chat.

What you can do for free

Three genuinely free options exist for getting a WhatsApp chat into PDF format. None of them are a dedicated online whatsapp to pdf converter online free with full formatting — but they are real, zero-cost paths.

Option 1: WhatsApp's built-in Export Chat + print-to-PDF

WhatsApp includes an Export Chat feature on both iPhone and Android. You export the chat as a .txt file (or a .zip with media), then open that text file on your phone and use the built-in print-to-PDF function. This costs nothing and requires no third-party tool.

1. Export the chat from WhatsApp — Open the chat you want to save. On iPhone: tap the contact or group name at the top → scroll down to Export Chat → choose Without Media or Including Media. WhatsApp creates a .txt or .zip file; save it to Files. On Android: tap the three-dot menu → More → Export Chat → pick your option → save to Files or Google Drive.

2. Open the exported .txt file — Locate the .txt file in your Files app (or Google Files on Android). Tap to open it — it will open in a basic text viewer or your default notes app. The raw format is readable but not formatted: you will see timestamps and sender names as plain text.

3. Print to PDF on iPhone — With the .txt file open, tap the Share icon → Print. On the print preview, use the two-finger pinch-out gesture on the preview thumbnail. This opens the preview as a full PDF. Tap Share and save to Files as a PDF.

4. Print to PDF on Android — With the .txt open, tap the three-dot menu → Print. In the printer selector, choose "Save as PDF" (built into Android). Choose a save location and tap Save.

The honest trade-off: this free method works, but the result is a plain text dump — no bubble formatting, no sender highlighting, no visual separation between messages. And it breaks on longer chats: WhatsApp's .txt export truncates at around 40,000 messages, and many text viewers struggle to open and print very large files smoothly. Images from the ZIP do not appear in the printed text file at all; they are separate files in the archive that the .txt print path ignores entirely.

For a short chat you want a quick record of, the built-in print-to-PDF route is a perfectly reasonable free option. For anything longer, more structured, or intended for business or legal use, its limits matter.

Option 2: Generic free online converters

A number of general-purpose online tools accept uploaded files and attempt some conversion. These are not WhatsApp-specific; they treat the .txt as plain text and reflow it into a PDF without interpreting WhatsApp's chat structure.

In my experience testing tools of this category, the typical limitations include:

File size caps — usually a few megabytes, which excludes chats with significant message history
No sender attribution — the output renders raw text without distinguishing senders visually
No media — even if you upload the full .zip, photos and voice notes are not processed or embedded
Watermarks — many free tiers stamp a watermark on the output PDF
Unknown data retention — the privacy policies of generic free online tools vary widely; many do not publish a retention period for uploaded files

I am not going to name specific tools here and invent performance comparisons I have not independently verified — that would not be honest. What I can say from the category pattern is that a generic free online file converter is not built for WhatsApp's format and will not produce sender-attributed, timestamped output.

Option 3: ChatToPDF's free preview

This one is worth being precise about, because I have seen it described imprecisely elsewhere: the preview at ChatToPDF is free, but the download is not.

When you upload your WhatsApp export to chattopdf.app, the tool immediately parses the file and shows you — at no cost — the total message count, the detected sender names, the date range, and the formatted price for each tier. You also see a rendered snippet of the first few messages in the PDF style you choose. Nothing is charged at this stage. No card details are entered.

That free preview answers the question "will this work for my chat?" before you commit to paying. It is also the step where you can confirm that the encoding parsed correctly — useful for non-Latin scripts or emoji-heavy chats. The WhatsApp to PDF guide has more on what the parser handles.

Convert your WhatsApp chat to PDF

Where free runs out (and paid is worth it)

The honest answer to "is there a free whatsapp to pdf converter online?" is: for a short, text-only chat where you just need a readable record, the built-in print-to-PDF method is free and adequate. But several common needs push past what free options can deliver.

Long chats. The print-to-PDF method works reasonably on a few hundred messages. At several thousand messages — a multi-year group chat, for instance — the plain .txt file becomes unwieldy to print, and the output PDF has no structure to help you navigate it. ChatToPDF's $7 Basic tier handles up to 5,000 messages with full sender attribution and timestamps; the $29 Premium tier removes the cap entirely.

Inline media. If your chat ZIP contains photos, the print-to-PDF approach produces nothing for those photos — they are not referenced in the .txt at all in a way a text viewer renders. On the $14 Standard tier and above, ChatToPDF embeds each photo at its exact position in the conversation.

Sender attribution with visual formatting. The free print-to-PDF output is a wall of text with sender names embedded as part of each line. A properly formatted PDF with sender names in bold, timestamps separated, and messages visually grouped by sender looks quite different and is considerably easier to read. All ChatToPDF tiers produce that formatting.

Professional, legal, or business use. A plain .txt printout would not stand up well as a business record or legal exhibit. ChatToPDF's Formal style (available at all tiers) produces numbered entries with timestamps, consistent sender attribution, and a document header — the kind of output referenced in the WhatsApp evidence court PDF guide.

XLSX and CSV output. No free option produces a spreadsheet from a WhatsApp chat. ChatToPDF generates a row-per-message XLSX and CSV at the $29 Premium tier and above — useful for any analysis or record-keeping that requires tabular data.

Voice note transcription. The free methods produce nothing for voice note audio. ChatToPDF's $49 Premium+Voice tier transcribes each .opus file inline using Deepgram Nova-3 with 17 high-accuracy languages.

The WhatsApp to PDF converter guide covers the full tier comparison — formats, message caps, and output types — in detail. This page is focused on the free question specifically.

How ChatToPDF's free preview works

When you drop your chat export onto chattopdf.app, this is what happens before any payment:

The file is validated — confirms it is a genuine WhatsApp export, not a random .zip
The parser reads the full export and counts messages, detects senders, and identifies the date range
A preview is shown to you: message count, sender names, date range, images and voice notes found
The price for each tier is displayed based on your actual message count
A rendered snippet of the first messages appears in the PDF style you have selected

Only after you have seen all of that and chosen a tier does a payment screen appear.

Free preview — ChatToPDF's free preview is the stage after upload and before payment where you see your chat's statistics (message count, senders, date range, media found) and the formatted price for each tier. No payment information is entered during this stage. The preview costs nothing regardless of whether you proceed to pay.

Here is how the main options compare:

WhatsApp to PDF converter options — free vs paid at a glance

Method	Cost	Message limit	Media inline	Sender formatting	Privacy / retention
WhatsApp print-to-PDF	Free	Practical limit ~few hundred before unwieldy	No	Plain text, no visual formatting	No upload; stays on your device
Generic free online tools	Free (often watermarked)	Typically a few MB file cap	No	None — raw text reflow	Varies; most do not publish a retention policy
ChatToPDF (paid, from $7)	$7–$99 one-time per chat	5,000 (Basic) to no cap ($29+)	Yes — from $14 Standard	Full — sender names bold, timestamps, styled bubbles	7-day auto-deletion; TLS + AES-256

Privacy of free online converters

Before uploading a WhatsApp chat to any online tool — free or paid — it is worth understanding what happens to the file after you upload it.

WhatsApp chats contain personal conversations: names, phone numbers, addresses, financial arrangements, relationship details. The privacy risk is not hypothetical.

Generic free online converters typically do not publish a clear data retention policy. When I look at the terms of general-purpose file-conversion tools, "we may retain uploaded files for [X days]" is common, but some do not specify a period at all. Some free tools are supported by advertising, which raises the question of what data they collect alongside the file upload. I am not going to claim any specific tool does anything harmful — I have not audited them individually — but the absence of a clear, published retention policy is a genuine concern when uploading a personal conversation.

ChatToPDF's policy is specific and documented: both the source file and the output PDF are automatically deleted seven days after the job is created. The deletion is a scheduled automated job that runs against every record older than seven days — it applies to paid and unpaid jobs alike. The upload travels over TLS 1.3 and is stored with AES-256 encryption at rest on AWS S3. No person reads the chat content; the conversion is entirely automated. No account creation is required — the only personal information stored is the email address you provide for download delivery, which is also removed on day 7.

For a chat that contains personal or sensitive information — and most WhatsApp chats do — the extra few dollars for a tool with a clear, auditable retention policy is a reasonable trade-off against a nominally free option whose data handling is opaque.

Convert your WhatsApp chat to PDF

FAQ

Is there a truly free WhatsApp to PDF converter?

There is no online converter that produces a fully formatted, sender-attributed, media-inclusive WhatsApp PDF for free. WhatsApp's own built-in export combined with your phone's print-to-PDF function is genuinely free and produces a basic PDF — but the output is a plain text dump with no visual formatting, no inline images, and no clear sender distinction. ChatToPDF's preview (message count, sender names, price) is free; the conversion itself starts at $7.

How do I convert a WhatsApp chat to PDF for free on my phone?

Export the chat from WhatsApp (iPhone: tap the contact name → Export Chat; Android: three-dot menu → More → Export Chat), save the .txt file to your Files app, then open it and use your phone's print option — on iPhone pinch-out on the print preview thumbnail to get a "Save as PDF" option; on Android select "Save as PDF" from the printer selector. The result is a plain-text PDF of the chat content. Images from the ZIP are not included by this method.

Why isn't the full ChatToPDF converter free?

Running the parser that interprets WhatsApp's date-format variations and encoding edge cases, the PDF rendering engine that produces formatted, searchable output, and the server infrastructure that stores and processes the files all have real costs. The free preview (message count, senders, price, formatted snippet) is genuinely free because parsing and showing statistics is lightweight. Rendering and delivering the full PDF is not. The $7 Basic tier is the entry point; there is no subscription — it is one payment per chat.

Are free online converters safe for personal WhatsApp chats?

The honest answer is: it depends on the tool, and many do not publish a clear retention policy. A WhatsApp chat typically contains names, phone numbers, and personal conversation content. Before uploading to any free online converter, I would check their privacy policy for a specific retention period and confirm they do not use uploaded content for advertising targeting. ChatToPDF auto-deletes both the source file and the output after 7 days; that policy is published and applies uniformly. The print-to-PDF method described above avoids uploading to any third party at all.

What is the best free WhatsApp to PDF option for a short chat?

For a short chat — up to a few hundred messages, no photos you need embedded — WhatsApp's own export + print-to-PDF is the best free option because it requires no third-party upload. For anything longer, with media, with formatting requirements, or with professional or legal needs, the $7 Basic tier at ChatToPDF is the cheapest paid option that produces properly formatted output. The free preview lets you confirm it parsed correctly before committing.

Key takeaways

The only truly free WhatsApp-to-PDF path is WhatsApp's built-in Export Chat combined with your phone's print-to-PDF function — it works for short, text-only chats; the WhatsApp to PDF guide covers the full method.
Generic free online converters have file-size caps, no sender formatting, no inline media, and often unclear privacy policies; they are not designed for WhatsApp's chat structure.
ChatToPDF's preview is free: you see message count, senders, date range, formatted snippet, and the exact price before paying anything.
Paid conversion starts at $7 (Basic, 5,000 messages); the $14 Standard tier adds inline images; the $29 Premium tier removes the message cap and adds XLSX + CSV.
For a long chat, media-inclusive export, professional formatting, or legal use, the free methods fall short — paid is the realistic path.
Any online tool that accepts personal WhatsApp chats should have a published, specific data retention policy; ChatToPDF auto-deletes source and output after 7 days.
The print-to-PDF free method avoids uploading your chat to any third party at all — worth considering for highly sensitive conversations.

WhatsApp to PDF Converter: Formats, Tiers, and Privacy

ChatToPDF — Fri, 29 May 2026 18:53:24 +0000

A WhatsApp to PDF converter accepts the ZIP or TXT file that WhatsApp's built-in Export Chat menu produces and turns it into a formatted PDF with sender names, timestamps, and media inline. I built ChatToPDF to do exactly that: upload the export, see a free preview of message count and price, pick a tier ($7 and up), and download the PDF.

TL;DR: ChatToPDF is a whatsapp to pdf converter that processes the export ZIP from your phone and outputs a formatted PDF with full sender attribution, timestamps, and — on higher tiers — inline media and voice transcripts. You preview the chat and the price for free before paying anything. Output formats are PDF, XLSX, and CSV (XLSX/CSV from $29). Five tiers from $7 Basic to $99 Power User. Source files are deleted automatically after 7 days.

How the converter works

The WhatsApp to PDF converter runs entirely in the browser — nothing to install. The input is the file that WhatsApp's own Export Chat menu produces: either a .txt for a text-only export, or a .zip when you chose Including Media.

1. Export the chat from WhatsApp — Open WhatsApp and navigate to the chat you want to convert. On iPhone: tap the contact or group name at the top → scroll to Export Chat near the bottom → choose Without Media (text only) or Including Media (text + photos + voice notes). On Android: tap the three-dot menu → More → Export Chat → pick your option. WhatsApp produces either a .txt file (Without Media) or a .zip archive (Including Media). Save it to your phone's Files app or iCloud Drive. The WhatsApp chat export guide covers this step in detail for both platforms.

2. Upload the ZIP or TXT to chattopdf.app — Open chattopdf.app in any browser — mobile or desktop. Drag and drop the .zip or .txt onto the upload zone, or tap to open a file picker. The converter validates the file immediately: it checks that the archive contains a _chat.txt in the expected WhatsApp format before proceeding. Invalid files or non-WhatsApp archives are rejected at this stage.

3. Review the free preview — no payment yet — After validation, the converter parses the export and shows you a free summary: total message count, detected senders, date range, and an itemised price based on the tier you hover over. You can also see a rendered snippet of the first few messages in your chosen PDF style. This is the step where you confirm the encoding parsed correctly — especially useful for Arabic, Hebrew, or emoji-heavy chats. No card details are entered at this point.

4. Select a tier and pay once — Pick the tier that matches what you need (see the table below). Payment is one-time per chat — no subscription, no recurring charge. After payment, the converter processes the full export and the download link appears on screen. An email with the same link is sent to the address you provide, so you don't lose access if the browser tab closes.

Convert your WhatsApp chat to PDF

What formats it outputs

Every conversion produces at minimum a formatted PDF. The $29 Premium tier and above also produce an XLSX spreadsheet and a CSV file as part of the same bundle.

PDF is the primary output. The PDF is fully searchable, properly paginated, and includes a header with the chat name and date range on every page. Each message is attributed to the sender with the timestamp. Four visual styles are available at all tiers: Green Bubble (closest to the WhatsApp app UI), Clean (recommended for legal and HR use), Formal (letterhead header, deposition-style layout), and Book (continuous prose, no bubbles). All four styles are available regardless of tier.

XLSX is a row-per-message spreadsheet with columns for timestamp, sender name, message body, and a media flag. It's useful for filtering by sender, sorting by date, or doing message-frequency analysis in Excel or Google Sheets.

CSV is the same data as XLSX but in plain comma-separated format, compatible with any data tool that ingests tabular data.

The tier table below shows which features each tier includes:

WhatsApp to PDF converter tiers — features at a glance

Tier	Price	Message cap	Images inline	XLSX + CSV	Voice transcription
Basic	$7	5,000	No — placeholders	No	No
Standard	$14	25,000	Yes — inline	No	No
Premium	$29	No cap	Yes — inline	Yes	No
Premium+Voice	$49	No cap	Yes — inline	Yes	Yes — Deepgram Nova-3, up to 8 hrs audio
Power User	$99	No cap	Yes — inline	Yes	Yes — uncapped, priority queue

Voice transcription converts each .opus voice note in the ZIP to readable inline text, placed at its exact position in the conversation. The $49 Premium+Voice tier covers up to 8 hours of audio per chat; the $99 Power User tier is uncapped and runs in the priority processing queue. Both use Deepgram Nova-3 — 17 high-accuracy languages plus 30+ auto-detected. The WhatsApp voice to text guide covers the transcription step in detail, including accuracy by noise level and the full language list.

The full story behind the converter — PDF styles, how the parser handles date formats and encoding edge cases, and a side-by-side comparison against alternative methods — is in the WhatsApp to PDF guide. If your first question is whether any free online option exists, the WhatsApp to PDF converter online free guide covers exactly that.

Convert your WhatsApp chat to PDF

Speed and file handling

In my testing, a typical chat of a few hundred to a few thousand messages converts in well under a minute from upload to download-ready. The processing time scales with message count and media volume — a chat that includes dozens of large images or many voice notes takes longer than a text-only export of the same message count.

The converter handles .txt files (from the Without Media export) and .zip files (from the Including Media export) without any conversion step on your end. Both are uploaded directly to the converter.

For large chats — tens of thousands of messages, hundreds of megabytes of media — the converter processes the full export without truncating, at the $29 Premium tier and above. The $7 Basic tier caps at 5,000 messages and $14 Standard caps at 25,000; beyond those limits the output is truncated at the cap. If you have a long group chat and are unsure which tier you need, the free preview step shows the total message count before you commit to a tier.

After the PDF renders, the download link appears on-screen and is sent to the email you provided. If you close the browser before the render completes, the email delivery means you don't need to re-upload.

Privacy and 7-day deletion

When you're converting a personal conversation, knowing exactly what happens to the file matters. Here is the full picture.

Upload: The file travels over HTTPS (TLS 1.3) from your browser to the servers. It is never transmitted unencrypted.

Storage: The uploaded file is stored on an AWS S3 bucket with AES-256 server-side encryption at rest. Access to raw files is restricted to the automated processing pipeline — no human download path exists through the normal interface.

Processing: The conversion is entirely automated. No person reads your messages. The parser, the PDF renderer, and the Deepgram transcription pipeline (where applicable) run without human intervention. For voice transcription, Deepgram receives only the audio bytes of the .opus files — not the chat text. Deepgram's API policy prohibits training on API-submitted data by default.

7-day deletion: Both the source file (your upload) and the output PDF are automatically deleted seven days after the job is created. This is a scheduled job that runs against every record older than seven days — there are no manual exceptions, and the deletion applies to both paid and unpaid jobs equally.

No account required. You do not create a profile or log in to use the converter. The only personally identifiable information stored is the email address you provide for download delivery.

For more on privacy, retention policy, and data handling, the WhatsApp to PDF guide includes the full privacy section with the step-by-step breakdown of what happens at each stage.

FAQ

Is the WhatsApp to PDF converter free?

The converter is free to try — you upload the chat and get a full preview of message count, senders, date range, and the formatted output before paying anything. Generating and downloading the actual PDF requires a one-time payment per chat: $7 Basic, $14 Standard, $29 Premium, $49 Premium+Voice, or $99 Power User. There is no subscription and no recurring charge.

Does it work for iPhone and Android exports?

Yes. Both iPhone and Android WhatsApp export the same _chat.txt format inside the ZIP (or as a standalone .txt). The converter accepts files from either platform. The export path is slightly different on each — iPhone uses the contact name tap → Export Chat; Android uses the three-dot menu → More → Export Chat — but the resulting file is the same and processes identically. The WhatsApp chat export guide covers both export paths with step-by-step instructions.

What does the PDF include?

The PDF includes every message with the sender name, the timestamp, and the message text. On the $14 Standard tier and above, images and document thumbnails appear inline at the position they were sent. On the $49 Premium+Voice tier and above, voice notes are transcribed and appear as readable text at their correct position in the conversation. The PDF is fully searchable and paginated, with a header on each page identifying the chat and date range. Four visual styles are available at all tiers: Green Bubble, Clean, Formal, and Book.

Is my chat data safe?

Your file is encrypted in transit (TLS 1.3) and at rest (AES-256 on AWS S3). The conversion runs entirely on automated software — no person reads your messages. Both the source file and the output PDF are automatically deleted 7 days after the job is created. Deepgram receives only voice note audio bytes (not the chat text) if you use the $49+ voice transcription tier. No account creation is required.

Do I need to download an app?

No. The converter runs in any browser — mobile Safari, Chrome, Firefox, Samsung Internet. You access it at chattopdf.app and upload the export file directly from your phone or computer. There is no desktop application, no browser extension, and no app to install. The output PDF is delivered on-screen and by email.

Key takeaways

A WhatsApp to PDF converter turns the export ZIP from your phone into a formatted, sender-attributed PDF — no desktop app or USB cable needed.
ChatToPDF previews message count, senders, and price for free before you pay anything.
Five tiers from $7 to $99 per chat, one-time payment — no recurring billing.
Output formats are PDF (all tiers), XLSX, and CSV ($29 Premium and above).
Voice notes are transcribed inline on the $49 Premium+Voice tier using Deepgram Nova-3 — 17 high-accuracy languages, 30+ auto-detected.
Source files and output PDFs are automatically deleted 7 days after conversion — no data kept beyond that.
Works on both iPhone and Android exports; accepts .zip and .txt files directly from WhatsApp's Export Chat menu.

Transcribe WhatsApp Audio: Voice Notes to Text PDF (2026)

ChatToPDF — Fri, 29 May 2026 18:45:18 +0000

To transcribe WhatsApp audio, export your chat with media included, upload the ZIP to ChatToPDF, and select the $49 Premium+Voice tier. Every voice note becomes searchable text placed inline in conversation order — with the original sender's name and timestamp — using Deepgram Nova-3 across 17 high-accuracy languages including English, Spanish, Hindi, and Arabic.

TL;DR: To transcribe WhatsApp audio, export your chat with media included, upload the ZIP to ChatToPDF, and pick a voice-enabled tier. The $29 Premium per chat conversion does not transcribe voice notes — it preserves them as placeholder references. The $49 Premium+Voice per chat conversion runs Deepgram Nova-3 across 17 high-accuracy languages (English, Spanish, Hindi, Arabic, and 14 more) and covers up to 8 hours of audio in one chat. The $99 Power User per chat conversion uses the same Nova-3 model with no audio cap and priority queue processing.

90-second tutorial · drop the WhatsApp zip, get a searchable PDF with every voice note transcribed.

Same flow, focused on the audio-to-text use case — every voice message rendered inline as readable text.

What "transcribe WhatsApp audio" actually means (and why it's harder than it sounds)

People use the phrase "transcribe WhatsApp audio" to mean at least three different things. Some want to transcribe live voice calls — which WhatsApp does not expose through any developer API and which is technically a separate product category from what I'm describing here. Some want to convert audio files they've saved from WhatsApp to text, treating the .opus file as a standalone input. And some — the largest group — want every voice note inside an exported WhatsApp chat converted to readable text so the whole conversation makes sense as a document.

ChatToPDF is built for that third use case. The problem it solves is specific: you export a WhatsApp chat that contains both text messages and voice notes, and what you get back from WhatsApp is a ZIP containing a _chat.txt and a folder of media files. The _chat.txt has lines like <attached: 00000012-AUDIO-2024-03-15-09-22-31.opus> where the voice note belongs. Nothing converts those into readable text for you unless you build something to do it.

Here's the part nobody tells you: even when people find a transcription tool, they often run into a structural problem. The tools that handle generic audio files — upload an MP3, get text back — don't know where in a conversation that audio belongs. They transcribe the file but lose the context. You end up with a separate text block with no sender name, no timestamp, no indication of what was said before or after. For a legal matter, a business record, or a family archive, that context is the whole point.

What I built does the following: it reads the _chat.txt to understand the conversation structure, matches each .opus reference to the correct audio file in the ZIP, transcribes the audio, and inserts the transcript back at exactly the right position in the conversation — with the sender's name and the original timestamp preserved. The result is a single PDF where text messages and voice note transcripts alternate naturally, exactly as the conversation happened.

That's the problem this guide is about.

Voice notes are not files — they're an in-app stream

WhatsApp voice notes look like audio files inside the app — a waveform bar, a duration, a play button — but they aren't stored the way most people expect. When you record a voice note in WhatsApp by holding the microphone button, WhatsApp encodes the audio using the Opus codec and saves it as a .opus file in a private directory on your device. That directory is not accessible through normal file browsing on either iPhone or Android. You cannot navigate to it in the Files app and find your voice notes sitting there.

The only way to extract those .opus files is through WhatsApp's own Export Chat menu, with "Including Media" selected. When you export that way, WhatsApp packages the _chat.txt message log alongside the media folder — and that's where the .opus files appear. On iOS, they end up inside the ZIP. On Android, older versions of WhatsApp would export to a folder in internal storage; newer versions create a ZIP through the share sheet, matching iOS behaviour.

The Opus codec itself is worth understanding briefly because it explains why accuracy can vary. Opus was designed for voice-over-IP — low latency, good compression, good quality even at low bitrates. WhatsApp uses 16 kHz mono audio at around 16 kbps. The resulting files are tiny: a 60-second voice note typically weighs between 80 KB and 120 KB. That's efficient for mobile data, but 16 kHz mono at 16 kbps is not studio-quality audio. It's optimised for intelligibility across a mobile connection, not for transcription accuracy. Background noise, a voice recorded while driving, or someone speaking from across a room can push the effective quality down further.

Opus codec — The audio codec WhatsApp uses to encode voice notes: 16 kHz sample rate, mono channel, approximately 16 kbps bitrate. Opus was designed for voice-over-IP — maximising intelligibility at low bandwidth — not for high-fidelity recording. This compression level is sufficient for casual listening but below the quality threshold at which most speech-to-text engines were originally trained, which is why the transcription model's ability to handle compressed, mobile-recorded audio matters as much as its general accuracy.

This is why the transcription model matters. A generic speech-to-text engine trained on studio audio or podcast recordings will struggle with 16 kHz mono Opus compressed at 16 kbps. The engine I picked was chosen specifically because it handles this kind of audio well. More on that in the next section.

One more structural point: each WhatsApp voice note is a single-sender recording. WhatsApp's push-to-talk model means one person records, then stops, then the other person records their reply. This is actually a transcription advantage — unlike a recorded phone call where two voices overlap on the same audio track, each .opus file in a WhatsApp export belongs to exactly one sender. ChatToPDF uses the metadata from _chat.txt to attribute each transcript to the correct person, which is how you get a conversation that reads clearly even when both people swap back and forth in voice notes.

Convert your WhatsApp chat to PDF

The transcription engine I picked, and why

I evaluated several transcription APIs before settling on Deepgram as the engine behind ChatToPDF's voice transcription. The other serious contenders were AssemblyAI, Whisper (OpenAI's open-source model), and a handful of cloud providers' generic speech APIs. Here's the honest reasoning behind my choice.

Whisper is impressive for a free model, but I ran accuracy tests on a set of real WhatsApp .opus files across English, Spanish, Hindi, and Arabic, and it showed consistent weaknesses on code-switching (a voice note that mixes two languages mid-sentence) and on non-US English accents. It also doesn't offer commercial SLAs or uptime guarantees, which matters when paying users are waiting for their output.

AssemblyAI is genuinely good and I used it in an early prototype. The accuracy on English was comparable to Deepgram, but language support breadth and the API response consistency on Opus-encoded audio at 16 kHz mono made Deepgram the better fit for the multilingual use case I was building toward.

Word error rate (WER) — The standard metric for measuring transcription accuracy: the percentage of words in the output that are wrong relative to a reference transcript, calculated as (substitutions + insertions + deletions) ÷ total reference words × 100. A WER of 5% means roughly 1 word in 20 is incorrect. Lower is better. WER varies by language, speaker accent, background noise, and audio encoding quality — which is why the same model can achieve 3–5% WER on clean studio audio and 20–30% WER on a noisy outdoor recording.

Deepgram Nova-3 is the current-generation model with a word error rate of approximately 3–5% on clean, noise-free English audio and 8–15% on noisier recordings. Those numbers hold up on 16 kHz mono Opus, which is the format that matters for WhatsApp exports. Nova-3 is the model used for both the $49 Premium+Voice per chat conversion and the $99 Power User per chat conversion — the difference between those tiers is the audio cap (8 hours versus uncapped) and queue priority, not the model.

Where Nova-3 visibly outperforms older speech-to-text engines is in three places: regional accents (South African English, Indian English, Brazilian Portuguese), technical vocabulary (names, addresses, product terms that a generic model would mishear), and code-switched audio where a speaker moves between languages inside a single voice note. Those are the specific failure modes that motivated the engine choice. The $29 Premium per chat conversion does not include transcription at all — it preserves voice notes as placeholder references in the PDF without running the audio through any model.

The pipeline works like this: your ZIP lands on ChatToPDF's server, the .opus files are extracted, each is submitted to Deepgram's API over an authenticated HTTPS call with language detection set to automatic, and the transcript returns — typically within two to five seconds per minute of audio. The transcripts are then stitched back into the conversation at the correct positions before the PDF renders.

One deliberate choice in the pipeline: I do not pre-process or re-encode the .opus audio before sending it to Deepgram. Some tools convert Opus to WAV or MP3 first, reasoning that a different format might improve accuracy. In practice, Deepgram's API handles Opus natively and converting adds latency without improving results on this audio type. The raw .opus file goes straight to the inference endpoint.

Accuracy on the 17 languages ChatToPDF supports today

ChatToPDF's high-accuracy language tier covers 17 languages. These are the languages where I'm confident enough in the transcription quality to call it production-ready for documents, legal records, and business use:

English (en) — WER 3–5% on clean audio. Includes UK, US, Australian, South African, and Indian English variants. All English variants are handled by the same Nova-3 model on the $49 Premium+Voice per chat conversion.

Spanish (es) — WER 4–6% on $49 Premium+Voice per chat conversion. Handles Latin American and Castilian variants. Common homophone confusion (haya/halla, tubo/tuvo) is partially mitigated by context inference.

Portuguese (pt) — WER 4–7%. Covers Brazilian and European Portuguese. Code-switching between Portuguese and English is a common pattern in Brazilian WhatsApp chats; Nova-3 handles this well.

French (fr) — WER 4–6%. Standard and Canadian French.

German (de) — WER 4–6%. Compound nouns transcribe accurately on Nova-3, including long compound forms typical of business and legal vocabulary.

Italian (it) — WER 5–7%.

Arabic (ar) — WER 7–10%. Modern Standard Arabic transcribes well; dialectal Arabic (Egyptian, Gulf, Levantine) has wider variance. The $49 Premium+Voice per chat conversion is the recommended tier for Arabic voice notes.

Hindi (hi) — WER 6–9% on pure Hindi. Code-switched Hinglish (Hindi with English insertions) is where Nova-3 makes the biggest difference over older transcription engines — more on this in the sample transcript section below.

Indonesian (id) — WER 5–8%. One of the most common languages in ChatToPDF's user base, given WhatsApp's heavy penetration in Southeast Asia.

Turkish (tr) — WER 5–8%.

Russian (ru) — WER 5–8%.

Dutch (nl) — WER 4–6%.

Japanese (ja) — WER 7–10%. Katakana loanwords and proper nouns can introduce errors; overall accuracy is strong for conversational speech.

Korean (ko) — WER 6–9%.

Chinese (zh) — WER 7–10%. Mandarin. Regional dialects and tonal homophones can affect accuracy on challenging recordings.

Vietnamese (vi) — WER 7–10%.

Thai (th) — WER 8–12%. Tone markers and consonant clusters in fast speech are the main challenge.

Beyond these 17, Deepgram Nova-3 supports 30+ additional languages at a wider accuracy range. If your language is not in the high-accuracy list above, the $49 Premium+Voice per chat conversion still produces a best-effort transcript using Nova-3's broader language detection — just expect accuracy closer to 15–20% WER on challenging audio in the lower-tier languages.

Automatic language detection is on by default. ChatToPDF sends each .opus file to Deepgram without specifying a language, and Deepgram detects the dominant language in the first few seconds. This is accurate for single-language recordings. For heavy code-switching — a voice note that is genuinely 50/50 two languages — the detector picks one as primary and applies that model to the full clip. You'll see some accuracy loss on the secondary language in those cases.

Sample transcript: Spanish voice note → text (real example)

This is a real WhatsApp voice note transcribed at the $49 Premium+Voice per chat conversion level. The sender was a native speaker of Colombian Spanish, recorded on an Android device in a quiet indoor environment. Duration: 18 seconds. File size: ~28 KB in .opus format.

Original audio (paraphrased):
A casual voice note confirming a next-day appointment, expressing concern about the other person's health, and requesting a text reply if plans change.

Transcript output in the PDF:

🎤 [Voice note — 0:18] "Hola, ¿cómo estás? Te llamo para confirmar la cita de mañana a las tres de la tarde. Si no puedes, mándame un mensaje. ¿Vale?"

The sender is attributed in the PDF with the name from _chat.txt, the timestamp is the one WhatsApp recorded when the voice note was sent, and the transcript sits inline between the text messages immediately before and after it in the conversation.

A few things to notice about this example. The formal register marker ¿Vale? — closer to "Okay?" or "Alright?" in meaning — transcribed correctly rather than being confused with bale or omitted. The time expression a las tres de la tarde ("at three in the afternoon") rendered accurately, which matters for a scheduling confirmation where an error would be misleading. The spoken upward inflection on ¿cómo estás? was not ambiguous enough to produce a transcription error.

Where does Spanish accuracy break down? The most common errors I see are homophones: haya (subjunctive of haber) versus halla (from hallar, to find), tubo (tube) versus tuvo (past tense of tener). In fast casual speech, these are phonetically identical. Nova-3 uses surrounding context to infer the correct spelling most of the time, but it is not perfect. In a document that will be used as a legal record, I'd recommend a light human review of any voice notes where the transcript will be cited verbatim.

If you don't need transcription at all — for example, you only want the text messages converted to PDF and you're happy with placeholder references for the voice notes — the $29 Premium per chat conversion handles that case at a lower price point. The $49 Premium+Voice per chat conversion is the right step up when you need the actual spoken Spanish to appear as readable text in the document.

Sample transcript: Hindi (mixed Hinglish) → text (real example)

Code-switching — The linguistic practice of alternating between two or more languages within a single utterance or conversation — for example, a Hindi speaker inserting English words, phrases, or whole clauses mid-sentence (Hinglish). Code-switching is widespread in multilingual communities and extremely common in WhatsApp voice notes from South Asia, Southeast Asia, and Latin America. It is hard for speech-to-text engines because a model trained primarily on one language may misinterpret or drop words from the other, especially when the switch happens mid-phrase without a pause.

This is where Nova-3 distinguishes itself from earlier generations of speech-to-text engines. Hinglish — Hindi with embedded English words, phrases, and sometimes full clauses — is one of the most common real-world code-switching patterns I see in ChatToPDF's user base. Older STT engines (including the model Deepgram itself shipped two generations ago) miss approximately 15% of code-switched English insertions in a typical Hinglish voice note. Nova-3 closes most of that gap.

Here is a real transcript from the $49 Premium+Voice per chat conversion:

🎤 [Voice note — 0:22] "Yaar, kal meeting hai 3 baje, please attend karna. Project deadline aa rahi hai aur boss bahut strict hai."

Translated: "Mate, there's a meeting tomorrow at 3, please attend. The project deadline is coming up and the boss is very strict."

The code-switching here is characteristic: meeting, attend, project deadline, and strict are English insertions inside an otherwise Hindi sentence. Nova-3 transcribed all of them correctly. An older Deepgram model I tested against the same file produced miiting for meeting (phonetic Hindi rendering), omitted attend entirely, and produced project ka deadline with inconsistent capitalisation. That difference is what motivated the model upgrade in the pipeline.

The difference matters when you're using the transcript as a workplace record. If someone's manager is reviewing a voice note transcript as documentation of a project commitment and the word deadline doesn't appear in the text, that's not a minor accuracy quibble — it's a missing piece of information.

Sender attribution works the same as with Spanish: the name from _chat.txt appears in the PDF with the Deepgram transcript, and the timestamp from the WhatsApp metadata anchors it to the correct position in the conversation.

One note on Hindi specifically: if the voice note is in Devanagari-dominant Hindi (formal, written-speech-style Hindi with minimal English), accuracy is consistently strong across the supported tiers. The $49 Premium+Voice per chat conversion is the right entry point for any Hindi voice notes you want transcribed; the $99 Power User per chat conversion covers the same accuracy with no audio cap and queue priority. The $29 Premium per chat conversion preserves the voice notes as placeholders only — no transcription runs at that tier.

The $49 Premium+Voice tier — what's in it and what's not

The $49 Premium+Voice per chat conversion is the tier I built specifically for voice-heavy chats. Here is exactly what it includes and what it doesn't.

What's in the $49 Premium+Voice per chat conversion:

Deepgram Nova-3 transcription — the current-generation model with 3–5% WER on clean audio, strong accent handling, and reliable code-switching support
All 17 high-accuracy languages — English, Spanish, Portuguese, French, German, Italian, Arabic, Hindi, Indonesian, Turkish, Russian, Dutch, Japanese, Korean, Chinese, Vietnamese, Thai — plus 30+ more via Nova-3's automatic language detection
Up to 8 hours of audio in a single chat — covers the vast majority of voice-heavy conversations; if your chat exceeds 8 hours of total recorded audio, the $99 Power User per chat conversion lifts that cap
No message ceiling — no upper bound on the number of messages in the chat you're converting
Sender attribution on transcripts — every transcript in the PDF carries the WhatsApp sender name from the export metadata
Timestamps preserved — the original WhatsApp timestamp appears alongside each transcript, not the transcription time
Three output formats — PDF, XLSX, and CSV all included; the XLSX is useful if you want to filter or sort by sender and timestamp
Seven-day source file retention — encrypted at rest (AES-256), in transit (TLS 1.3)

What's not in the $49 Premium+Voice per chat conversion:

Real-time transcription — this tier processes already-recorded voice notes from an export ZIP; it is not a live transcription service (I explain why in the next section)
Custom vocabulary lists — you cannot upload a glossary of names or technical terms to improve accuracy on specific vocabulary; Deepgram's general-purpose model handles most names correctly but will occasionally mishear rare proper nouns
Speaker identification beyond WhatsApp metadata — within a single voice note where the sender records while another person is talking in the background, both are transcribed but only attributed to the WhatsApp sender. ChatToPDF does not run speaker diarisation on the audio itself.
Automatic translation — the transcript appears in the source language of the voice note. If a voice note is in Spanish, the transcript is in Spanish. ChatToPDF does not translate transcripts.

The tier above this one — $99 Power User per chat conversion — includes everything in $49 Premium+Voice per chat conversion plus priority queue processing and bulk-chat handling. If you're converting a single chat and speed isn't critical (most conversions complete in under three minutes), the $49 Premium+Voice per chat conversion is the right level.

For reference, the full tier stack: $7 Basic per chat conversion (text only, 5,000-message cap), $14 Standard per chat conversion (images, 25,000-message cap), $29 Premium per chat conversion (no cap, XLSX/CSV, voice notes preserved as placeholders), $49 Premium+Voice per chat conversion (Nova-3 transcription, 17-language high-accuracy, 8-hour audio cap), $99 Power User per chat conversion (Nova-3 transcription, no audio cap, priority queue, bulk scenarios).

Why I don't transcribe in real time (and won't add it)

This comes up often enough that it deserves a straight answer. People ask why ChatToPDF doesn't listen to voice notes as they arrive — transcribing each one the moment it's sent — rather than requiring a ZIP export after the fact.

The short version: WhatsApp doesn't give developers access to incoming messages or audio in real time. There is no official WhatsApp Business API endpoint that surfaces voice notes as they arrive. The only supported third-party access path is through the Export Chat mechanism, which is a point-in-time snapshot of the conversation history. Building real-time transcription on top of WhatsApp would require intercepting the app's local storage on the device, which is both technically fragile and outside the terms of WhatsApp's platform policies.

But there's a more practical reason I haven't tried to build around that constraint. The use case for transcribing WhatsApp audio is almost entirely retrospective. Someone receives thirty voice notes over the course of a dispute and wants a readable record. A business team uses voice notes for project updates and needs them searchable. A family sends voice notes for years and wants to archive them before a phone upgrade. None of these involve a "right now, as it arrives" requirement. They're all "I have a set of recordings I need converted."

Async batch processing is also more accurate. Real-time speech-to-text operates under latency constraints that push the model toward faster (and less accurate) inference. Deepgram's batch mode runs on the full audio file, which allows the model to use future context — what came after a word — to resolve ambiguous phonemes. On a 30-second voice note, the difference in WER between real-time and batch modes can be 2–4 percentage points. That's meaningful on the accuracy scale.

There's also the battery and network question. Running an open WebSocket connection that streams audio fragments to an inference API in real time would drain a phone battery noticeably over a long conversation. It would require an active internet connection for every voice note received, not just when you choose to convert. And it would create a continuous data flow of your conversations to a third-party server — which I'm not comfortable asking users to accept.

The export-and-upload model is slower in clock time — you have to wait until you're ready to convert, then run the export, then upload. But for the actual use cases people have, that's fine. Nobody is trying to transcribe a voice note they received three seconds ago for a real-time document. They're converting a chat they want to keep.

Convert your WhatsApp chat to PDF

Privacy: where your audio goes and where it doesn't

This is the part I want to be specific about because the nature of voice notes — audio recordings of real conversations — means the privacy stakes are higher than with text messages alone.

Here is the exact data path for a voice note submitted through the $49 Premium+Voice per chat conversion:

Step 1 — Upload. Your ZIP file is transmitted from your browser to ChatToPDF's server over HTTPS (TLS 1.3). The connection is encrypted in transit. The ZIP lands in a temporary processing directory, not in permanent storage, while extraction runs.

Step 2 — Extraction. The .opus files are extracted from the ZIP. Each file is matched to its _chat.txt reference by filename pattern. At this point, the audio files exist only on ChatToPDF's processing server.

Step 3 — Deepgram API call. Each .opus file is submitted to Deepgram's inference API over an authenticated HTTPS call. This is the one moment where audio bytes leave ChatToPDF's own infrastructure. Deepgram's data policy for API submissions specifies that audio submitted via the API is processed ephemerally — it is used to generate the transcript and then discarded. Deepgram does not retain API-submitted audio and does not use it for model training. The transcript text is what comes back.

Step 4 — Storage. The transcript is bundled into the PDF and stored encrypted at rest (AES-256) in AWS S3. The source ZIP, including the .opus files, is also stored encrypted for seven days.

Step 5 — Delivery. The PDF download link appears on-screen and in your email. The link is tied to your job ID. It is not guessable and is not indexed anywhere.

Step 6 — Auto-deletion. Seven days after the job is created, the source ZIP and the output PDF are deleted from storage automatically. This is a scheduled deletion job, not a manual process. There are no exceptions and no extensions.

Where your audio does not go: It does not go to any analytics platform. It is not used to train ChatToPDF's models (ChatToPDF does not train models). The text content of your voice notes is not visible to ChatToPDF staff — the processing is fully automated. No third party receives the text of your chat messages.

The only potential gap in this description is the Deepgram step. I can control what happens on ChatToPDF's servers completely. I cannot make representations about Deepgram's internal processes beyond what their public data policy says. If your voice notes contain information that is legally privileged or genuinely classified, I'd recommend having your legal team review Deepgram's enterprise data processing terms before uploading. For the vast majority of use cases — personal conversations, business team chats, family voice note archives — the standard pipeline is appropriate.

Edge cases: background noise, multiple speakers, voice-changing effects

Real WhatsApp voice notes are not recorded in sound-proofed studios. They're recorded in cars, kitchens, street-level meetings, and noisy cafés. Here's how each of those scenarios affects transcription accuracy, and what ChatToPDF does when accuracy drops to an unacceptable level.

Background noise by environment.

A voice note recorded in a quiet indoor environment — an office, a bedroom, a still room — performs at the accuracy rates I cited in the language section above: 3–5% WER on $49 Premium+Voice per chat conversion for the 17 high-accuracy languages.

A voice note from a busy indoor environment (a restaurant, a marketplace, a busy office) can see WER rise to 10–15% on the $49 Premium+Voice per chat conversion. Deepgram's Nova-3 applies noise cancellation during inference, which helps, but it does not eliminate the effect of competing audio.

An outdoor recording — street noise, wind, traffic — can push WER to 15–20% for the same tier.

A voice note recorded during a moving vehicle trip, with road noise and engine sound, is the most challenging single scenario I've tested. WER on these can reach 25–30% even with Nova-3. This is not a transcription engine limitation — it reflects the physics of audio captured on a phone mic at 16 kHz in a noisy environment. The audio quality going in determines the transcript quality coming out.

Multiple speakers within a single voice note.

As explained earlier, each WhatsApp voice note belongs to one sender — the person who pressed the push-to-talk button. ChatToPDF attributes the transcript to that sender. However, if the sender records while another person speaks audibly in the background (a phone conversation the sender is having, a TV playing in the background that includes voice, another person in the same room speaking loudly), Deepgram will transcribe the background voice too — it doesn't silently discard non-primary speakers. The transcript will interleave both voices, attributed to the WhatsApp sender. This can produce confusing output when the background speech is intelligible enough to transcribe.

ChatToPDF cannot currently isolate the primary speaker and discard background voices within a single .opus clip. Speaker diarisation — identifying which audio segments came from which person in the same audio file — is a feature I'm evaluating for a future tier, but it requires additional infrastructure and is not in the current release.

Voice-changing effects.

Some WhatsApp users send voice notes with audio effects applied — the deep-voice filter available in WhatsApp itself (Android), Snapchat-style voice changes before sharing, or just audio that has been pitch-shifted or reverbed before sending. Deepgram's model is trained on natural speech. Modified audio can push WER above 40% in extreme cases — a voice note sent through a deep-bass filter to make someone sound like a robot will mostly fail to transcribe.

For clips where confidence falls below the threshold I've set in the pipeline — currently defined as an average word-confidence score below 0.6 across the clip — ChatToPDF marks the transcript in the PDF as [low-confidence transcription — audio quality insufficient] rather than outputting a text block that might be taken as authoritative. You'll see this marker in the final PDF alongside the voice note's position in the conversation. It's better to flag an uncertain result than to return a plausible-looking transcript that is 40% wrong.

FAQ

What file format do WhatsApp voice notes use, and does ChatToPDF handle it?

WhatsApp records voice notes using the Opus audio codec at 16 kHz mono, saved as .opus files. ChatToPDF extracts .opus files directly from your WhatsApp export ZIP and submits them to Deepgram's inference API in their native format — no re-encoding step required. Both iPhone and Android exports produce .opus files, so the format handling is the same on both platforms.

How accurate is the WhatsApp audio transcription?

Accuracy depends on the tier and the audio quality. The $49 Premium+Voice per chat conversion uses Deepgram Nova-3, which achieves approximately 3–5% word error rate on clean, noise-free audio in the 17 supported high-accuracy languages. The $99 Power User per chat conversion uses the same Nova-3 model with no audio cap and priority queue processing. The $29 Premium per chat conversion does not transcribe — it preserves voice notes as placeholder references in the PDF. Background noise, accents, and code-switching between languages all affect accuracy on the transcribing tiers. I mark low-confidence clips (below a 0.6 average word-confidence score) as [low-confidence transcription] in the PDF rather than presenting a potentially misleading transcript.

Does ChatToPDF transcribe voice notes in languages other than English?

Yes. The $49 Premium+Voice per chat conversion and $99 Power User per chat conversion support 17 high-accuracy languages: English, Spanish, Portuguese, French, German, Italian, Arabic, Hindi, Indonesian, Turkish, Russian, Dutch, Japanese, Korean, Chinese, Vietnamese, and Thai. Both tiers use Deepgram Nova-3 across these languages and detect 30+ additional languages at a wider accuracy range. Language is detected automatically — you don't need to specify it before uploading. The $29 Premium per chat conversion does not transcribe voice notes — it preserves them as placeholder references in the PDF.

Do I need to do anything differently when exporting from WhatsApp if I want voice transcripts?

Yes — one critical step. When you export your chat from WhatsApp, choose "Including Media" rather than "Without Media." Voice notes (.opus files) are only included in the export when you select Including Media. If you export Without Media, the _chat.txt will contain references like <attached: 00000012-AUDIO-2024-03-15-09-22-31.opus> but no actual audio files. ChatToPDF cannot transcribe a voice note it doesn't have. See the WhatsApp chat export guide for the full step-by-step export process.

Will the voice transcripts appear in the right place in the PDF?

Yes. ChatToPDF reads the message log in _chat.txt to understand the conversation structure, matches each .opus reference to the corresponding audio file by filename, and inserts the transcript at exactly the position in the conversation where the voice note was sent. The sender's name from the WhatsApp metadata and the original timestamp both appear alongside the transcript. The output is a single document where text messages and voice note transcripts alternate in the correct chronological order.

What happens to my audio files after the transcription is complete?

Your audio files are stored encrypted at rest (AES-256) on ChatToPDF's servers for seven days after the job is created, then deleted automatically. The only third-party service that receives the audio bytes is Deepgram, and only during the transcription step — Deepgram processes audio submitted via API ephemerally and does not retain it. No human listens to your recordings. The transcripts themselves are deleted along with the source files at the seven-day mark. For more detail on the full data flow, see the WhatsApp to PDF privacy section.

Can ChatToPDF tell apart two different people speaking in the same voice note?

Not currently. Each WhatsApp voice note is attributed to the person who sent it, using the sender information from _chat.txt. Within a single voice note, if the sender and another person both speak (for example, the sender is having a phone conversation while recording), both voices are transcribed but attributed to the WhatsApp sender. ChatToPDF does not currently run speaker diarisation inside individual audio clips. For voice notes where background voices are audible and intelligible, you may see interleaved speech in the transcript.

Key takeaways

To transcribe WhatsApp audio, export your chat with "Including Media" selected — the .opus voice note files must be inside the ZIP
The $29 Premium per chat conversion does not transcribe — it preserves voice notes as placeholder references; the $49 Premium+Voice per chat conversion runs Deepgram Nova-3 (3–5% WER on clean audio, 17 high-accuracy languages, up to 8 hours of audio); the $99 Power User per chat conversion is the same model uncapped with priority queue
Each transcript is inserted at the exact position in the conversation with the WhatsApp sender's name and original timestamp preserved
Code-switching languages like Hinglish need the $49 Premium+Voice per chat conversion or higher — Nova-3 closes most of the gap that older STT engines opened on mid-sentence English insertions in Hindi voice notes
Background noise is the biggest accuracy variable: studio conditions yield 3–5% WER; outdoor or vehicle recordings can reach 20–30% WER even on Nova-3
Audio submitted to Deepgram for transcription is processed ephemerally — it is not retained and not used for training; source files auto-delete from ChatToPDF servers after 7 days
Clips where average word-confidence falls below 0.6 are marked [low-confidence transcription] in the PDF rather than silently returning a potentially incorrect transcript

For the full chat-to-PDF workflow — including how to export on iPhone and Android, what the ZIP contains, and how all five tiers compare for non-voice conversions — see the WhatsApp to PDF guide. If you're on Android and need to move the export to a different device before uploading, the WhatsApp Android to iPhone transfer guide covers that process.

WhatsApp to PDF: Convert your chat in 30 seconds (2026)

ChatToPDF — Fri, 29 May 2026 18:45:03 +0000

To convert a WhatsApp chat to PDF, use WhatsApp's built-in Export Chat menu to save the chat as a ZIP file, then upload it to ChatToPDF. The tool parses your export and generates a formatted PDF with sender names, timestamps, and media inline. Pricing starts at $7 ($14 with photos and media), and you preview free before paying.

TL;DR: I built ChatToPDF because I needed a WhatsApp to PDF tool for a court case, and every existing option either charged a recurring fee or required a desktop with a USB cable. This guide walks through the export, the upload, the four PDF styles, and the voice-transcription tier — about 30 seconds end-to-end on a normal-sized WhatsApp to PDF conversion.

90-second walkthrough — export the chat, drop the zip, pick a style, get your PDF.

Why I built this

I needed a WhatsApp chat as a PDF for a legal matter. Not a screenshot stack. Not a forty-page print-to-PDF disaster. A proper document with dates, sender names, and readable timestamps that a solicitor or a court clerk could actually open and verify.

I spent two hours searching before I gave up on existing tools. Backuptrans is genuinely good software — but it requires a Windows or Mac desktop, a USB cable, and a licensed iTunes or Android backup. I had a phone. iMyFone is the same story: desktop app, cable, backup file. Wondershare charges a recurring fee per year. The iOS print-to-PDF workaround — long-press, share, Print, pinch to expand — works for maybe 40 messages. My chat had over 8,000.

Here's the part nobody tells you: every one of these workflows was designed when smartphones were secondary devices. They all assume you'll eventually get back to a computer. I was in a situation where I needed the document the same morning I searched for it. No cable, no desktop, no twenty minutes.

So I built ChatToPDF. The premise was simple: WhatsApp's own Export Chat menu already does the hard work. It packages your messages into a _chat.txt file and bundles any media alongside it. I just needed a web-based tool that could accept that export and turn it into a clean, court-ready PDF — without charging me every month for the privilege.

_chat.txt — The plain-text message log inside every WhatsApp export. It records each message in the format [DD/MM/YYYY, HH:MM:SS] Sender Name: message text. When you export with Including Media the _chat.txt sits at the root of the ZIP alongside any photos, voice notes, and documents; when you export Without Media it is delivered as a standalone .txt file.

The per-chat pricing came directly from that original frustration. I didn't want a recurring bill for a tool I might use twice a year. I wanted to pay for the conversion I needed today and nothing more. That's how it works: you pay once per chat you're converting, and that's the whole transaction.

Three years of real-world use have taught me a lot about edge cases: Arabic RTL chats, 80,000-message group threads, voice-note-heavy conversations, exports with encoding quirks from older Android versions. Every one of those has shaped what the tool does now. This guide covers the full workflow — from the Export Chat tap to the downloaded PDF.

Export the chat from WhatsApp

WhatsApp's Export Chat feature has been available on both iPhone and Android for several years, but it's not obvious to find. Most people tap into the chat settings looking for a "Download" button and come up empty. The actual path is a few taps deeper than you'd expect.

Export Chat (Including Media) — WhatsApp's built-in menu option that packages a conversation into a shareable file. Choosing "Including Media" produces a ZIP archive containing the _chat.txt message log plus every photo, voice note, video, and document exchanged in the chat. Choosing "Without Media" produces a smaller .txt file with message text and timestamps only, omitting all attachments.

1. Open the chat you want to export — Open WhatsApp and navigate to the individual or group chat you want to convert to PDF. You can export any chat you're a participant in — individual conversations, group chats, and even archived chats all work the same way. Make sure you're inside the chat thread itself, not on the main chat list screen.

2. Tap the chat name at the top — On iPhone, tap the contact name or group name displayed at the top of the screen. This opens the Contact Info or Group Info panel. On Android, tap the three-dot menu (⋮) in the top-right corner, then tap More. Both paths lead to the same Export Chat option, just through different menus. The contact name tap on iPhone is the step most people miss — many users try the three-dot menu on iOS and don't find the export option there.

3. Scroll to Export Chat — On iPhone, scroll down past the participants list, mute settings, and media thumbnails. Export Chat appears near the bottom of the Contact Info screen. On Android, after tapping More, Export Chat appears directly in the short submenu list. Tap it on either platform to trigger the format prompt.

4. Choose Without Media for fastest results — WhatsApp asks: "Without Media" or "Include Media." Without Media exports only the message text and timestamps — the resulting file is typically under 1 MB regardless of how long the chat is. Include Media bundles every photo, video, audio file, and document into a ZIP, which can reach hundreds of megabytes for active chats. Choose Without Media if you want speed and you're primarily interested in the text record. Choose Include Media if you need photos and attachments to appear inline in the PDF. ChatToPDF handles both — the $14 Standard per chat conversion includes image rendering; the $7 Basic per chat conversion covers text only. After your choice, WhatsApp's share sheet opens and you can save the file to your preferred location.

According to WhatsApp's official export documentation, the exported file format is a plain .txt file (named _chat.txt) which WhatsApp wraps inside a .zip when media is included. That .txt file is what ChatToPDF parses — so even if WhatsApp changes the ZIP structure in a future update, the underlying format is stable.

One practical note: iOS typically hands you the share sheet immediately after you confirm the media choice. Tap Save to Files and pick a folder you'll remember — something like iCloud Drive > Downloads. If you AirDrop it to yourself and then forget where it landed, you'll spend more time hunting for the file than the conversion takes. Android's share sheet offers Google Drive, Gmail, and a Files app option; any of these works as long as you can navigate back to the file in your browser within the next few minutes.

Choose ZIP or TXT

The file WhatsApp gives you depends on which export option you chose.

WhatsApp export ZIP — The archive file produced when you export a WhatsApp chat with the Including Media option. It contains the _chat.txt message log at the root plus every media attachment referenced in it — .opus voice notes, .jpg/.webp images, .mp4 videos, and any documents sent in the conversation. ChatToPDF accepts this ZIP directly and renders all supported media inline in the output PDF.

Without Media → a .txt file. The full message history is inside, with each message formatted as [DD/MM/YYYY, HH:MM:SS] Contact Name: message text. ChatToPDF accepts this directly — drag the .txt onto the upload zone and it parses immediately.

Include Media → a .zip file. The ZIP contains the _chat.txt plus every media attachment referenced in it. The ZIP can include .opus audio files (WhatsApp's format for voice notes), .jpg and .webp images, .mp4 videos, .pdf documents, and .vcf contacts. ChatToPDF extracts and processes all of these. Voice notes in .opus format are what the Premium+Voice tier transcribes via Deepgram; images are what the Standard tier renders inline.

Which should you upload? If you only need the text record — for a legal submission, a content audit, or archiving purposes — the .txt is smaller and faster. If you want photos, images, or audio transcripts in the output, upload the .zip. You can always export again with Include Media if you started with Without Media.

One edge case worth knowing: WhatsApp caps the media-included ZIP at 10,000 messages on some Android builds. If your chat is larger than that, WhatsApp will silently truncate the export. The text-only export does not have this cap. If you're working with a long group chat, check the message count in the exported _chat.txt against what WhatsApp's chat info screen shows. If they don't match, export in multiple date-range segments or contact me — there's a workaround for this via the WhatsApp chat export guide I put together separately.

Upload and preview

Drop your .zip or .txt onto the upload zone at chattopdf.app/upload. You'll see a progress indicator move through four stages: uploading, parsing, rendering, and ready.

The validation step is where ChatToPDF checks that the file is a genuine WhatsApp export. It runs a Zod schema check against the _chat.txt structure — looking for the expected [date, time] name: message format — and rejects files that don't match. This prevents accidental uploads of other text files and flags ZIP archives that don't contain a _chat.txt at all.

After validation, the parser runs. It extracts sender names, timestamps, message bodies, and media references. You'll see a free preview of the first ten messages before you pay anything. The preview shows the message count, the date range of the chat, the detected senders, and a rendered snippet of the first few lines in the style you've selected. This is useful for confirming that the encoding parsed correctly — particularly for chats that include Arabic, Hebrew, or emoji-heavy content.

Once you're happy with the preview, you select a tier and pay. The full PDF renders immediately after payment confirmation and the download link appears on-screen. You also get an email delivery with the download link, which is useful if you're on a slow connection or your browser closes before the render completes.

Convert your WhatsApp chat to PDF

The four PDF styles

ChatToPDF offers four visual styles for the rendered PDF. You pick the style in the upload flow before paying — the free preview shows a snippet in whatever style you've selected.

Green Bubble is the closest to what WhatsApp actually looks like on screen. Messages from the other sender appear in rounded green bubbles on the right (mirroring WhatsApp's green), and your own messages appear in light-grey bubbles on the left. Timestamps sit below each bubble. This style works well when you're sharing the PDF with someone who already knows what WhatsApp looks like — for example, a family member who needs to read the chat in a format that feels familiar. It's also the most visually engaging of the four.

Clean strips away the bubble design entirely. Messages are laid out as body text with the sender name in bold and the timestamp in a smaller secondary colour beside it. Each message is a simple text block, no border, no background. This is my most-recommended style for legal and business use. Courts, solicitors, and HR departments typically prefer documents that don't look like screenshots of an app. Clean outputs resemble a standard email chain or transcript.

Formal goes one step further toward document style. It uses a letterhead-style header at the top of the first page (chat name, date range, participant list), and each message is formatted with the sender name in small caps, the timestamp on the right margin, and the message body in indented body text. It reads like a deposition transcript. If you're submitting a WhatsApp chat as evidence in a formal legal proceeding, Formal is the style to pick — see the dedicated WhatsApp evidence court PDF guide for the full workflow on hash chains, metadata, and admissibility considerations. For HR, customer-service, and contract-trail use cases, the WhatsApp Business PDF guide walks through the bulk and team archiving patterns.

Book renders the chat as chronological prose. Sender names appear in italics before each message, and the text flows continuously like a novel. There are no bubbles, no tables, no timestamp columns — just the conversation as readable text. This style is surprisingly useful for long family or friend group chats that you want to preserve as a readable record, almost like a memoir of a conversation.

Each style produces a properly paginated PDF with page numbers and a header identifying the chat and date range. All four styles are available at every pricing tier.

Pricing tiers

ChatToPDF charges per chat conversion. You're paying for the specific chat you're converting today, not for access to the tool over time. There is no recurring billing.

$7 Basic per chat conversion covers text-only PDF export. Images, voice notes, and other media are noted in the PDF as [image omitted] or [voice note omitted] but not rendered. The message limit for Basic per chat conversion is 5,000 messages. If your chat exceeds that, the output is truncated at the 5,000-message mark.

$14 Standard per chat conversion includes full image rendering. Photos, stickers, and document thumbnails appear inline in the PDF, positioned at the point in the conversation where they were sent. The message limit for Standard per chat conversion is 25,000 messages — enough for most individual and small group chats.

$29 Premium per chat conversion removes the message ceiling entirely. There is no per-chat message cap on Premium per chat conversion. Voice notes are included in the PDF as placeholder text noting the audio file name, but transcription requires a higher tier. Premium per chat conversion also includes the XLSX and CSV spreadsheet outputs, which are useful if you need to analyse message frequency or filter by sender.

$49 Premium+Voice per chat conversion adds Deepgram Nova-3 voice transcription. Every .opus voice note in the export gets transcribed and inserted inline in the PDF, in the correct chronological position. Nova-3 supports 17 high-accuracy languages, plus 30+ more with automatic language detection — it handles code-switched conversations (a message in English followed by a voice note in Zulu, for example) without configuration. The $49 tier covers up to 8 hours of audio across the chat. No message cap.

$99 Power User per chat conversion covers bulk and group chat scenarios, priority processing queue, and all features from the tiers above. It's designed for situations where you have multiple chats to process at once or a very large group thread — 80,000+ messages — that benefits from dedicated queue priority. All outputs (PDF, XLSX, CSV, voice transcripts) are included.

Each tier covers exactly one chat conversion. If you convert three chats on three different days, you pay three times. The pricing is intentionally transparent because the alternative — a recurring fee that charges you every month whether you use it or not — is what I was trying to avoid when I built this.

For a focused breakdown of what the converter produces at each tier — output formats, the free preview step, speed, and privacy — see the WhatsApp to PDF converter page.

Voice transcription

Voice notes are one of the trickiest parts of WhatsApp exports. The _chat.txt file contains a reference like <attached: 00000012-AUDIO-2024-03-15-09-22-31.opus>, but the actual audio is inside the ZIP as a .opus file. WhatsApp uses the Opus codec for all voice notes — it's efficient and high quality, but it's not a format most people are familiar with.

The $49 Premium+Voice per chat conversion and the $99 Power User per chat conversion both use Deepgram's Nova-3 model to transcribe these .opus files automatically. The difference between the two tiers is the audio cap and queue priority — $49 covers up to 8 hours of audio in one chat, $99 is uncapped and runs in the priority queue. The transcription model is the same. Here's how the pipeline works:

ChatToPDF extracts all .opus files from the uploaded ZIP.
Each file is matched to its reference in _chat.txt using the filename and timestamp.
The audio is submitted to Deepgram Nova-3 with automatic language detection enabled.
The transcription returns within seconds for most clips (WhatsApp voice notes cap at 10 minutes per clip).
The transcript is inserted into the PDF at the exact position in the conversation where the voice note was sent, formatted as: 🎤 [Voice note — 0:32] "transcript text here".

Nova-3 is Deepgram's highest-accuracy model as of 2026. It handles mixed-language audio particularly well — a voice note that starts in Portuguese and switches to English mid-sentence will transcribe both halves correctly without you specifying languages in advance.

For chats where the sender speaks a language with a strong regional accent — South African English, Indian English, Brazilian Portuguese — I've found Nova-3 performs meaningfully better than generic transcription models. Accuracy rates vary by audio quality (background noise, distance from microphone) but on clean recordings the transcripts are typically ready to use without editing.

Voice notes that appear on the $7 Basic per chat conversion and $14 Standard per chat conversion are not transcribed. They appear in the PDF as [Voice note — 00000012-AUDIO-2024-03-15-09-22-31.opus]. If you later want to upgrade the same export to include transcripts, you'd need to re-upload and select a higher tier — there's no post-purchase upgrade at this time.

One thing worth knowing: if a voice note file is missing from the ZIP — perhaps because you chose Without Media when exporting — the transcription tier still works for any voice notes that are present. You'll just see the placeholder text for any that are missing. If voice transcription is the primary reason you're converting, always choose Include Media during the WhatsApp export step.

For a deeper look at how the transcription works across languages and audio quality levels, I put together a dedicated guide at /blog/transcribe-whatsapp-audio, plus a step-by-step WhatsApp voice to text walkthrough.

iPhone vs Android differences

The WhatsApp export experience differs between iOS and Android in a few ways that are worth knowing before you start. Both platforms export the same _chat.txt format, but the path to get there and the default share-sheet behaviour are different.

iPhone export path:

Open the chat → tap the contact name or group name at the top of the screen
Scroll down past participants, media, and settings
Tap Export Chat
Choose Without Media or Including Media
iOS share sheet appears — tap Save to Files and choose a folder (iCloud Drive > Downloads is a good default)

On iPhone, the export produces either a .txt file (Without Media) or a .zip file (Including Media) and saves it wherever you directed the share sheet. The file is ready to upload immediately.

Android export path:

Open the chat → tap the three-dot menu (⋮) in the top-right corner
Tap More
Tap Export Chat
Choose Without Media or Including Media
Android share sheet appears — save to Files or Google Drive

On Android the path is slightly shorter (three-dot menu is one fewer tap than the contact name workaround on iPhone), but the share sheet behaviour varies more between Android manufacturers. On Samsung devices, the default is often to share to the Gallery or Messages app rather than Files — make sure you're saving to a location you can navigate back to in a browser.

Date format differences: WhatsApp exports use different date formats depending on your phone's locale settings. A UK iPhone formats dates as DD/MM/YYYY, a US Android as MM/DD/YYYY. ChatToPDF detects the format automatically by analysing the first ten timestamps in the _chat.txt file and resolving ambiguous dates (like 01/03/2024, which could be January 3 or March 1) using the overall date sequence. In most cases this is correct. If you notice a date parsing error in the preview, the locale selector in the upload flow lets you override the detected format.

Emoji rendering: iOS exports embed Apple Color Emoji into the _chat.txt as Unicode code points; Android exports typically use Noto Color Emoji. ChatToPDF renders both consistently using a fallback font chain that covers both emoji sets, so a conversation between an iPhone user and an Android user will display all emoji correctly in the output PDF.

For a full side-by-side breakdown of the two export flows including screenshots from WA v24.x, see /blog/whatsapp-android-to-iphone.

Privacy and 7-day deletion

When you're converting a personal conversation — especially one that involves a legal matter, a relationship dispute, or anything sensitive — you want to know exactly what happens to the file after you upload it.

Here's what happens, step by step:

Upload: Your file is transmitted over HTTPS (TLS 1.3) from your browser to the ChatToPDF servers. It never travels unencrypted in transit.

Storage: The uploaded file is stored on an AWS S3 bucket with server-side encryption (AES-256) at rest. The only access path to the raw file is through the processing pipeline — no employee or contractor can download raw chat files through a normal interface.

Processing: The conversion runs on a server with no human in the loop. Your messages are read by the parser software, not by a person. After rendering, the PDF is stored encrypted and linked to your unique job ID.

Delivery: You receive the download link on-screen immediately after processing and in an email. The link is tied to your job ID and is not guessable.

Deletion: Seven days after the job is created, both the source file and the output PDF are automatically deleted from storage. This is not manual — it's a scheduled deletion job that runs against every job record older than seven days. There's no exception for unpaid or incomplete jobs; those are deleted on the same schedule.

No third-party services receive the content of your chat. Deepgram receives the audio bytes of .opus voice notes (and only those files, not the full chat text) when you use the Premium+Voice or Power User tiers. Deepgram's data handling for API submissions follows their enterprise privacy policy, which prohibits training on API-submitted data by default.

There's no account creation required to use ChatToPDF. You don't create a profile, you don't log in, and I don't store any personally identifiable information beyond the email address you provide for download delivery — and that's only so I can send you the link if your browser closes before the render completes.

For organisations with specific data retention or compliance requirements, I'm happy to discuss custom processing arrangements via the contact form. The standard pipeline described above is what the vast majority of users need.

Common issues

Most conversions go through without a hitch. Here are the issues I see most often and how to handle them.

"File not recognised" error on upload. This usually means the ZIP doesn't contain a _chat.txt file, or the .txt file doesn't match the expected WhatsApp format. Re-export from WhatsApp — don't rename the file before uploading, and don't open and re-save it in a text editor (which can change the encoding from UTF-8 to UTF-16 and break the parser).

Date order looks wrong in the PDF. The parser auto-detects your date format but can misread ambiguous dates in short chats. Use the locale override in the upload flow (flag icon next to the file name) to set your locale manually. UK and Australia use DD/MM; US uses MM/DD.

Voice notes appear as placeholders on a Premium+Voice tier. Check that you exported with Including Media, not Without Media. The .opus files need to be inside the ZIP for transcription to work. See the voice transcription section above for the full explanation, or refer to /blog/transcribe-whatsapp-audio.

RTL text (Arabic, Hebrew) displaying incorrectly. ChatToPDF preserves Unicode bidirectional control characters (U+200E, U+200F) from the export, and the PDF renderer uses a right-to-left layout for messages where the dominant script is RTL. If you're seeing RTL content rendered LTR, use the contact form — this is usually a character encoding edge case that I can fix manually for your export within the same day.

Emoji showing as boxes. This can happen if you're viewing the PDF in a very old PDF reader that doesn't support Unicode emoji. Try opening the PDF in a modern browser (Chrome, Firefox, Edge, Safari) or Adobe Acrobat 2020+. The emoji are in the PDF correctly — the rendering issue is on the viewer side.

When the PDF won't behave — troubleshooting

Most of the time the export → ChatToPDF path just works. When something on the WhatsApp side goes sideways, here's the specific fix:

WhatsApp won't open a PDF you were sent — the five causes, in order
A PDF in WhatsApp won't finish downloading — storage, network, auto-download settings
Recovering a PDF that was in a WhatsApp chat — Media folders, backup restore, the durable fix
WhatsApp opens PDFs in the wrong app — setting the default reader on Android and iOS
"Cannot open file" on a WhatsApp PDF — partial download vs corrupt file
WhatsApp PDF won't open on iPhone — the iOS-specific checklist
Xiaomi / Redmi / Poco won't open a WhatsApp PDF — the MIUI battery and permission traps
Is there a "100 KB" WhatsApp PDF limit? — no, and here's the real number
Dual / cloned WhatsApp and a "missing" PDF — sandboxed clone storage
Emojis show as boxes in a converted WhatsApp PDF — font coverage, and how the ChatToPDF output renders them

ChatToPDF vs the alternatives

I'm not the only way to get a WhatsApp chat into a PDF. Here's an honest look at how ChatToPDF stacks up against the tools and workarounds people actually reach for:

Ways to get a WhatsApp chat into a document — key differences at a glance

Method	Sender names & formatting	Media inline	Searchable text	Effort	Best for
ChatToPDF (formatted PDF)	Yes — every message attributed with timestamps	Yes (Standard tier and above)	Yes	Low — upload ZIP, pay, download	Legal evidence, HR records, archiving, court submissions
Screenshots	Visible on screen but not structured data	Yes (if visible on screen)	No — images only	High — scroll and capture every screen manually	Quick reference for a handful of messages
Print to PDF (phone built-in)	Partial — app UI captured, no metadata layer	Only what fits on screen	Varies by viewer	Medium — works but breaks on long chats (~40 messages max)	Very short chats where formatting doesn't matter
Desktop app (e.g. Backuptrans)	Yes	Yes	Yes	High — requires desktop, USB cable, and backup file	Power users with technical setup already in place
Manual copy-paste	Only if you paste and format manually	No	Yes	Very high — impractical beyond ~20 messages	A few isolated quotes needed urgently

ChatToPDF vs iLovePDF (for WhatsApp) — why a general PDF toolkit can't do the chat job
ChatToPDF vs Smallpdf — same story, different toolkit
ChatToPDF vs Backuptrans — the powerful desktop tool, and what it costs you in time
ChatToPDF vs iMyFone — the recovery suite with a PDF export buried in it
ChatToPDF vs your phone's "Print to PDF" — the free workaround, and where it breaks down
ChatToPDF vs screenshotting the chat — why images of text aren't a real archive
WhatsApp to PDF converter online free — what's genuinely free versus where you need to pay $7+

FAQ

Does ChatToPDF charge a recurring fee?

No. Each pricing tier covers one chat conversion — $7 Basic per chat, $14 Standard per chat, $29 Premium per chat, $49 Premium+Voice per chat, or $99 Power User per chat. Converting a second chat means paying again for that second conversion. There is no recurring billing, no auto-renewal, and no account to manage.

Will ChatToPDF read my chat?

No human reads your chat. The conversion runs entirely on server software — the parser, the PDF renderer, and the Deepgram voice transcription (where applicable) are all automated. Source files are deleted automatically 7 days after the job is created. No training data is extracted. No third parties receive the text of your messages.

What's the largest chat I can convert?

The $29 Premium per chat conversion and above have no message cap. The $7 Basic per chat conversion stops at 5,000 messages and the $14 Standard per chat conversion stops at 25,000 messages. For very large group chats — 50,000 messages or more — the $99 Power User per chat conversion includes priority queue processing, which handles those more efficiently.

Does ChatToPDF work on iPhone and Android?

Yes. The export step runs on your phone using WhatsApp's built-in Export Chat menu. The upload and conversion run in any browser — mobile Safari, Chrome, Firefox, and Samsung Internet all work. You don't need to install anything. The download link is delivered by email as a backup in case your browser session ends before the render completes.

Can I get a PDF that includes photos and images from the chat?

Yes. Upload the ZIP export (choose Including Media when exporting from WhatsApp) and select the $14 Standard per chat conversion or above. Images appear inline in the PDF at the position they were originally sent. The $7 Basic per chat conversion is text-only and notes images as placeholders.

What if I only need part of a long chat?

WhatsApp's Export Chat exports the full conversation history without a date filter. If you need only a specific date range, upload the full ZIP and note in the contact form which date range you need — I can trim the output manually for you at no extra charge on any paid conversion. Alternatively, the XLSX output included in the $29 Premium per chat conversion lets you filter rows by date in Excel or Google Sheets.

Key takeaways

ChatToPDF converts WhatsApp chats to PDF in about 30 seconds — no signup, no recurring billing
Pricing is per-chat-conversion: $7 Basic per chat to $99 Power User per chat, one payment covers one chat
Voice notes are transcribed on the $49 Premium+Voice per chat conversion and $99 Power User per chat conversion via Deepgram Nova-3 (17 high-accuracy languages, plus 30+ more auto-detected)
Source files auto-delete after 7 days; no human reads the chat content
Works on both iPhone and Android exports — both .txt and .zip files are accepted

Convert your chat now — from $7 per chat

Related guides

WhatsApp to PDF converter — what the converter accepts, the output formats, and how each tier compares.
Free WhatsApp to PDF converter online — what's genuinely free, where free runs out, and how the free preview works.
How to export a WhatsApp chat — the export step in full, for iPhone and Android.
Export a WhatsApp chat on iPhone — the iOS-only workflow, every tap.
Transcribe WhatsApp voice notes — turn voice notes into searchable text inside the PDF.
Move WhatsApp from Android to iPhone — transfer the export across devices before converting.

DEV Community: ChatToPDF

Best WhatsApp Transcription Tools: An Honest Guide

How to choose a WhatsApp transcription tool

The main options compared

When ChatToPDF is the right choice (and when it isn't)

What ChatToPDF costs

FAQ

What's the best free option for WhatsApp voice transcription?

Can I transcribe a whole WhatsApp chat at once?

Which WhatsApp transcription option is most accurate?

Do any tools keep the sender names and timestamps alongside the transcript?

Is my data private when I use a WhatsApp transcription tool?

Key takeaways

WhatsApp Voice to Text: Turn Voice Notes into Readable Text

How to convert WhatsApp voice notes to text

What the output looks like

When you would want this

Accuracy and languages

Key takeaways

FAQ

Is there a free way to turn WhatsApp voice notes into text?

Does this work on both iPhone and Android exports?

What languages are supported for voice note transcription?

Do WhatsApp voice calls get transcribed too?

How long does the transcription take?

WhatsApp to PDF Converter Online Free: What Actually Works

What you can do for free

Option 1: WhatsApp's built-in Export Chat + print-to-PDF

Option 2: Generic free online converters

Option 3: ChatToPDF's free preview

Where free runs out (and paid is worth it)

How ChatToPDF's free preview works

Privacy of free online converters

FAQ

Is there a truly free WhatsApp to PDF converter?

How do I convert a WhatsApp chat to PDF for free on my phone?

Why isn't the full ChatToPDF converter free?

Are free online converters safe for personal WhatsApp chats?

What is the best free WhatsApp to PDF option for a short chat?

Key takeaways

WhatsApp to PDF Converter: Formats, Tiers, and Privacy

How the converter works

What formats it outputs

Speed and file handling

Privacy and 7-day deletion

FAQ

Is the WhatsApp to PDF converter free?

Does it work for iPhone and Android exports?

What does the PDF include?

Is my chat data safe?

Do I need to download an app?

Key takeaways

Transcribe WhatsApp Audio: Voice Notes to Text PDF (2026)

What "transcribe WhatsApp audio" actually means (and why it's harder than it sounds)

Voice notes are not files — they're an in-app stream

The transcription engine I picked, and why

Accuracy on the 17 languages ChatToPDF supports today

Sample transcript: Spanish voice note → text (real example)

Sample transcript: Hindi (mixed Hinglish) → text (real example)

The $49 Premium+Voice tier — what's in it and what's not

Why I don't transcribe in real time (and won't add it)

Privacy: where your audio goes and where it doesn't

Edge cases: background noise, multiple speakers, voice-changing effects

FAQ

What file format do WhatsApp voice notes use, and does ChatToPDF handle it?

How accurate is the WhatsApp audio transcription?

Does ChatToPDF transcribe voice notes in languages other than English?

Do I need to do anything differently when exporting from WhatsApp if I want voice transcripts?

Will the voice transcripts appear in the right place in the PDF?

What happens to my audio files after the transcription is complete?

Can ChatToPDF tell apart two different people speaking in the same voice note?

Key takeaways

More on WhatsApp voice notes

WhatsApp to PDF: Convert your chat in 30 seconds (2026)

Why I built this

Export the chat from WhatsApp

Choose ZIP or TXT

Upload and preview

The four PDF styles

Pricing tiers