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Claude API Pricing Per Million Tokens: All Models (Oct 2026)

scorpion4ik26-lang — Fri, 16 Oct 2026 09:37:20 +0000

I am the founder of PromptUnit. This post first appeared on the PromptUnit blog, where it is kept up to date.

Claude API pricing is per million tokens (MTok), with separate rates for input and output. As of October 14, 2026, Anthropic's pricing page lists four current models: Claude Haiku 5.5 at $0.10 input and $0.50 output (for prompts up to 100,000 tokens), Sonnet 5.5 at $2 and $10, Opus 5.5 at $4 and $20, and Fable 5.1 at $10 and $50. The Batch API halves those prices, and a cache read costs between 2.5% and 10% of the input price, depending on the model.

This guide lists every model's rates, recomputes four common workloads on the current models with the arithmetic shown, and covers the costs that sit outside the per-token table: long prompts on Haiku 5.5, the tokenizer change, US-only inference, fast mode, web search and code execution. Every Claude price below comes from Anthropic's documentation, read on October 14, 2026.

Claude API prices for every current model

Anthropic's models overview names four current models. Sonnet 5 and Haiku 4.5 are now legacy models but still available, so they are in the table too. Prices are per million tokens on the Claude API with global routing, which is the default.

Model	Input	Output	Cache hit	Context window	Anthropic's description
Claude Fable 5.1	$10	$50	$0.25	1M	Demanding reasoning and long-horizon agentic work
Claude Opus 5.5	$4	$20	$0.20	1M	Long-running agentic coding and knowledge work
Claude Sonnet 5.5	$2	$10	$0.10	1M	The best combination of speed and intelligence
Claude Haiku 5.5, prompts up to 100K tokens	$0.10	$0.50	$0.01	1M	High-volume, latency-sensitive tasks such as classification, extraction and routing
Claude Haiku 5.5, prompts over 100K tokens	$0.50	$2.50	$0.05	1M	Same model, higher rates
Claude Sonnet 5 (legacy)	$2	$10	$0.20	1M	Anthropic suggests moving to Sonnet 5.5
Claude Haiku 4.5 (legacy)	$1	$5	$0.10	200K	Anthropic suggests moving to Haiku 5.5

A few things the table does not show:

Sonnet 5's price is now permanent. Sonnet 5 launched at $2 and $10 as introductory pricing through August 31, 2026. Anthropic has made that the standard price, and the planned rise to $3 and $15 on September 1 will not happen.
Thinking tokens are output tokens. Thinking is on by default on Fable 5.1, Opus 5.5, Sonnet 5.5, Sonnet 5 and Haiku 5.5, and it cannot be turned off on Fable 5.1 and Opus 5.5. Anthropic's thinking docs say the reasoning tokens are billed as output tokens even when the thinking text is not returned to you. The effort parameter is the control: Opus 5.5 and Haiku 5.5 default to medium, the other models to high, and low spends the fewest tokens.
Haiku 4.5 is legacy, not deprecated. Anthropic's model deprecations page lists its retirement as not sooner than October 15, 2026, and Anthropic gives at least 60 days' notice before retiring a publicly released model. It also has the smallest context window (200K) and needs at least 4,096 tokens before a prompt can be cached.

Legacy and retired models

Older models still run on the Claude API at their own prices unless they are marked retired.

Model	Status on October 14, 2026	Input	Output	Cache hit
Claude Fable 5	Legacy, still available	$10	$50	$1
Claude Opus 5	Legacy, still available	$5	$25	$0.50
Claude Opus 4.8, 4.7 and 4.6	Legacy, still available	$5	$25	$0.50
Claude Opus 4.5	Legacy, retirement not sooner than November 24, 2026	$5	$25	$0.50
Claude Sonnet 4.6	Legacy, still available	$3	$15	$0.30
Claude Sonnet 4.5	Deprecated, retires November 30, 2026	$3	$15	$0.30

Retired on the Claude API: Opus 4.1 and Sonnet 4 (Anthropic's pricing page lists them as retired except on Bedrock and Google Cloud), and Opus 4 and Haiku 3.5 (retired except on Google Cloud). Haiku 3.5 was retired on February 19, 2026, so Google Cloud is the only place Anthropic still lists for it.

Claude Mythos is a separate model, not another name for Fable

Claude Mythos 5.1 and Mythos 5 are separate models. They have the same listed token prices as Fable 5.1 and Fable 5, but they are available only to organizations verified through Anthropic's verification programs, such as the Cyber Verification Program. What Claude Mythos costs and how its price changed covers the details.

Same text, more tokens: the tokenizer change

Anthropic's pricing page says Claude 4.7 and later models use a newer tokenizer that produces approximately 30% more tokens for the same text, and that the exact increase depends on the content. Sonnet 4.6 and earlier models use the previous tokenizer, and the Haiku 5.5 overview says the same text counts as about 30% more tokens on Haiku 5.5 than on Haiku 4.5.

So per-token prices overstate the saving when you move from an older model to a newer one. These estimates assume the full 30%; your own content may differ:

Sonnet 4.6 to Sonnet 5.5. The per-token price drops by a third ($3 to $2 input, $15 to $10 output). With 30% more tokens, the same task costs 2 x 1.3 = 2.6 against 3, about 13% less. This is an estimate, not a measurement.
Haiku 4.5 to Haiku 5.5 (prompts up to 100K tokens). 0.10 x 1.3 = 0.13 against 1.00, about 87% less per task. Also an estimate.
Opus 4.6 or 4.5 to Opus 5.5. 4 x 1.3 = 5.2 against 5, about 4% more per task. An estimate again.
Opus 4.7 or 4.8 to Opus 5.5. Both sides use the newer tokenizer, so the same input costs 20% less. Output length still depends on the model and the effort setting.

To get your own number, run a sample of real prompts through the token counting endpoint with each model's ID.

What four common workloads cost on current models

Each scenario uses 30-day months and token counts as the priced model counts them. Output tokens include any thinking tokens.

Scenario 1: customer support chat. 500 input and 200 output tokens per call, 10,000 calls a day.

Haiku 5.5: input is 500 x 10,000 = 5 million tokens x $0.10 = $0.50 a day. Output is 200 x 10,000 = 2 million tokens x $0.50 = $1.00 a day. Total $1.50 a day, $45 a month.
Sonnet 5.5: 5 million x $2 = $10, plus 2 million x $10 = $20. Total $30 a day, $900 a month, 20 times the Haiku 5.5 bill.
If you run this on Haiku 4.5 today, it costs 5 million x $1 = $5 plus 2 million x $5 = $10, so $15 a day or $450 a month. If your 500 and 200 were counted on Haiku 4.5, expect about 650 and 260 on Haiku 5.5 (an estimate): 6.5 million x $0.10 = $0.65 plus 2.6 million x $0.50 = $1.30, so $1.95 a day, about $59 a month.

The price gap does not tell you whether Haiku 5.5 answers your customers well enough. Test it on a sample of your own conversations before you switch.

Scenario 2: code review assistant. 3,000 input and 800 output tokens per call, 1,000 calls a day.

Sonnet 5.5: 3 million x $2 = $6, plus 0.8 million x $10 = $8. Total $14 a day, $420 a month.
Opus 5.5: 3 million x $4 = $12, plus 0.8 million x $20 = $16. Total $28 a day, $840 a month.
Haiku 5.5: 3 million x $0.10 = $0.30, plus 0.8 million x $0.50 = $0.40. Total $0.70 a day, $21 a month.
Coming from Sonnet 4.6, the same counts cost 3 million x $3 = $9 plus 0.8 million x $15 = $12, so $21 a day or $630 a month. With 30% more tokens on Sonnet 5.5 (3,900 and 1,040 per call): 3.9 million x $2 = $7.80 plus 1.04 million x $10 = $10.40, so $18.20 a day or $546 a month. That is about 13% less, not the 33% the per-token prices suggest, and it is an estimate.

Scenario 3: long document analysis. 10,000 input and 2,000 output tokens per call, 100 calls a day.

Opus 5.5: 1 million x $4 = $4, plus 0.2 million x $20 = $4. Total $8 a day, $240 a month. At 1,000 calls a day: $80 a day, $2,400 a month.
Fable 5.1: 1 million x $10 = $10, plus 0.2 million x $50 = $10. Total $20 a day, $600 a month.
If the results can wait for the Batch API: $120 a month on Opus 5.5, $300 on Fable 5.1.

Scenario 4: very long prompts on Haiku 5.5. 150,000 input and 2,000 output tokens per call, 100 calls a day.

Above 100,000 prompt tokens, Haiku 5.5 charges $0.50 and $2.50: 15 million x $0.50 = $7.50, plus 0.2 million x $2.50 = $0.50. Total $8 a day, $240 a month.
At the lower rates the same tokens would cost 15 million x $0.10 = $1.50 plus 0.2 million x $0.50 = $0.10, so $1.60 a day. Crossing the threshold puts the whole request on the higher rates, which are 5 times the lower ones.
Sonnet 5.5 for the same work: 15 million x $2 = $30, plus 0.2 million x $10 = $2. Total $32 a day, $960 a month, so Haiku 5.5 still costs a quarter as much here.

The threshold is sharp. A 99,000-token prompt costs 99,000 x $0.10 / 1 million = $0.0099 of input; a 101,000-token prompt costs 101,000 x $0.50 / 1 million = $0.0505, about 5 times as much for 2% more text. Cache reads and cache writes count toward the 100,000, so caching part of a long prompt does not keep a request under it.

How prompt caching changes the bill

Prompt caching stores a prompt prefix so later requests read it at a fraction of the input price. There are two ways to turn it on. Automatic caching takes a single cache_control field at the top level of the request, and the cache point moves forward on its own as a conversation grows. Explicit breakpoints put cache_control on individual blocks, up to 4 per request.

Cache operation	Price relative to base input	Example per MTok
5-minute cache write	1.25x	Sonnet 5.5: $2.50
1-hour cache write	2x	Sonnet 5.5: $4
Cache read on Fable 5.1 (and Mythos 5.1)	0.025x	$0.25
Cache read on Opus 5.5 and Sonnet 5.5	0.05x	$0.20 and $0.10
Cache read on all other models	0.1x	Haiku 5.5: $0.01

A worked example: a 2,000-token system prompt on Sonnet 5.5, sent with 50,000 calls a day.

Without caching: 2,000 x 50,000 = 100 million tokens x $2 = $200 a day.
With caching: 100 million x $0.10 = $10 a day in cache reads. One cache write costs 2,000 x $2.50 / 1 million = $0.005. At about 35 calls a minute, the 5-minute cache rarely expires, because each read refreshes it at no extra cost.
The saving is about $190 a day, or $5,700 a month, on that part of the input.
The same prompt on Fable 5.1 costs 100 million x $10 = $1,000 a day uncached and 100 million x $0.25 = $25 a day from the cache.

Four rules from the prompt caching docs decide whether this works for you:

Minimum length. The cached prefix must be at least 512 tokens on Fable 5.1, Opus 5.5, Sonnet 5.5 and Haiku 5.5; 1,024 on Sonnet 5, Sonnet 4.6 and Opus 4.8; 2,048 on Opus 4.7; and 4,096 on Haiku 4.5, Opus 4.6 and Opus 4.5. Shorter prefixes are not cached, so a 500-token prompt like the one in Scenario 1 would not qualify.
Exact prefix. The cache covers tools, system prompt and messages, in that order, up to the breakpoint. A timestamp or user ID inside that prefix changes it on every request, and you pay for a fresh write each time.
Timing. The lifetime is counted from the start of the request that writes or reads the entry, not from the end of the response.
Break-even. Anthropic says that at the 0.1x read price, a 5-minute write pays for itself after one cache read and a 1-hour write after two.

The multipliers stack with the Batch API discount and with data residency pricing. For a side-by-side with OpenAI's caching, see prompt caching on OpenAI and Anthropic.

Batch API: half price if you can wait

The Message Batches API charges 50% of the standard price on input and output. Anthropic says most batches finish within an hour. Results are available once every request is done or after 24 hours, whichever comes first, and requests that are not processed within 24 hours expire without charge. One batch holds up to 100,000 requests or 256 MB.

Model	Batch input	Batch output
Claude Fable 5.1	$5	$25
Claude Opus 5.5	$2	$10
Claude Sonnet 5.5	$1	$5
Claude Haiku 5.5, prompts up to 100K tokens	$0.05	$0.25
Claude Haiku 5.5, prompts over 100K tokens	$0.25	$1.25
Claude Sonnet 5 (legacy)	$1	$5
Claude Haiku 4.5 (legacy)	$0.50	$2.50

Batch and caching discounts combine. Because a batch can take longer than 5 minutes, Anthropic suggests the 1-hour cache for context shared across a batch. Fast mode is not available with the Batch API. Which workloads to move to batch goes through the decision.

Costs outside the token table

Item	Price	Conditions
US-only inference (`inference_geo: "us"`)	1.1x every token price	Claude 4.6 and later models; global routing, the default, is standard price
Fast mode on Opus 5.5	$8 input, $40 output per MTok	Research preview, access by request, Claude API only; Opus 5 and Opus 4.8 are $10 and $50
Web search	$10 per 1,000 searches	Plus standard token prices for the results; a search that errors is not billed
Web fetch	No extra charge	You pay for the tokens of the fetched content
Code execution	1,550 free hours per organization per month, then $0.05 per hour per container	Free when the request includes `web_search_20260209` or `web_fetch_20260209` (or later); execution time has a 5-minute minimum
Claude Managed Agents	$0.08 per session-hour	Counted only while a session is running, plus tokens; no batch discount
Tool use system prompt	286 extra input tokens	On Opus 5.5, Sonnet 5.5 and Haiku 5.5 with `tool_choice` auto or none, plus your own tool definitions

What these look like in practice:

US-only inference puts Sonnet 5.5 at $2.20 input and $11 output. It applies to input, output, cache writes and cache reads, and on Haiku 5.5 also to the over-100K rates. Haiku 4.5 does not accept the parameter.
Fast mode gives up to 2.5x higher output tokens per second at twice Opus 5.5's standard price. Scenario 3 on fast mode would cost 1 million x $8 = $8 plus 0.2 million x $40 = $8, so $16 a day instead of $8.
Web search adds up in agents. Three searches per request at 1,000 requests a day is 3,000 searches x $0.01 = $30 a day, before the tokens of the results.
Free credits. Anthropic's pricing FAQ says new users receive a small amount of free credits to test the API. It does not state the amount.

On other platforms: Claude Platform on AWS and Microsoft Foundry bill the same per-token rates through their marketplaces, in Claude Consumption Units at $0.01 each. Amazon Bedrock and Google Cloud set their own prices; for Claude 4.5 models and later, Anthropic's pricing page says their regional and multi-region endpoints cost 10% more than global ones. Claude on AWS Bedrock vs the Anthropic API compares the two.

Claude vs OpenAI at each price point

The OpenAI prices below come from OpenAI's pricing page on October 14, 2026: standard tier, prompts up to 272K input tokens. Models are paired by price, not by quality.

Price point	Claude model	Input / output	Cache read	OpenAI model	Input / output	Cached input
Lowest	Haiku 5.5	$0.10 / $0.50	$0.01	GPT-6 Luna	$0.10 / $0.50	$0.01
Middle	Sonnet 5.5	$2 / $10	$0.10	GPT-6.1 Sol	$2 / $10	$0.10
Upper	Opus 5.5	$4 / $20	$0.20	GPT-5.6 Sol	$4 / $20	$0.40
Top	Fable 5.1	$10 / $50	$0.25	GPT-6 Astra	$10 / $50	$1.00

The list prices match at every level. The differences are elsewhere:

Cache reads. Fable 5.1 reads from cache at $0.25 against GPT-6 Astra's $1.00, and Opus 5.5 at $0.20 against GPT-5.6 Sol's $0.40. OpenAI says GPT-5.6 Sol's price is promotional and available at least through November 21, 2026.
Long prompts. OpenAI charges more above 272K input tokens: GPT-6.1 Sol goes to $4 and $15, GPT-6 Astra to $20 and $75, GPT-6 Luna to $0.20 and $0.75. Fable 5.1, Opus 5.5 and Sonnet 5.5 keep the same price up to 1M tokens. Haiku 5.5 goes the other way: its higher rates start at 100K, so for a prompt between 100K and 272K tokens, GPT-6 Luna costs $0.10 and $0.50 while Haiku 5.5 costs $0.50 and $2.50.
Data residency. OpenAI also adds 10% for regional processing endpoints on models released on or after March 5, 2026.
Tokens are not the same unit. Each vendor has its own tokenizer, so the same text is a different number of tokens on each. Equal per-token prices do not mean equal cost per task. Count tokens on a sample of your own prompts on both sides.

Picking a tier

Price alone does not pick the model. Anthropic suggests starting with Opus 5.5 for most workloads and using Fable 5.1 when your evals on Opus 5.5 at higher effort still fall short, and it describes Haiku 5.5 as built for classification, extraction and routing. Before you pay for a bigger model, try a lower effort setting on the one you have: effort changes how many output tokens every response uses.

A practical test: run 200 to 500 representative inputs through two tiers, score the answers on your own criteria, then apply the prices above. Claude Haiku vs Sonnet: routing guide and the LLM model routing guide cover how to make that call per request instead of once for the whole app.

Where PromptUnit fits

PromptUnit makes that choice per request. Each request is checked: when a cheaper model is just as good for that request, PromptUnit uses it; otherwise the request goes to the model you asked for. If you connected keys for more than one provider, the cheaper model can be at another of those providers. Setup is two settings: point your app's AI API base URL at PromptUnit and add your PromptUnit key (the x-promptunit-key header). Your own Anthropic key stays. The dashboard shows every request: the model asked for, the model that answered, what it cost and what it saved. It is free until it has saved you money, then it takes 20% of what it saves.

The cheapest model per token is not always good enough. In one app the PromptUnit team runs itself (checks up to October 12, 2026, small samples, judged by Claude Sonnet 5, the model the app asked for, so not an independent judge), Claude Haiku 4.5 served the web-research step for five days with no errors and answers that passed the automatic format checks, yet it was judged worse than Sonnet 5 in 2 of 3 checks. PromptUnit stopped moving that step and kept it on Sonnet 5. Claude Haiku 5.5 was judged as good in only 4 of 8 checks on the same step. On the same app's video-prompt step, GPT-5.4 mini was judged as good in 23 of 23 checks at about 73% lower cost.

For a step-by-step plan to act on these numbers, see How to Reduce Claude API Costs: A Practical 5-Step Guide.

FAQ

How much does the Claude API cost?

As of October 14, 2026, Anthropic lists Claude Haiku 5.5 at $0.10 per million input tokens and $0.50 per million output tokens (prompts up to 100,000 tokens), Sonnet 5.5 at $2 and $10, Opus 5.5 at $4 and $20, and Fable 5.1 at $10 and $50. The Batch API halves these prices.

What is the cheapest Claude model?

Claude Haiku 5.5: $0.10 per million input tokens and $0.50 per million output tokens for prompts up to 100,000 tokens. A request whose prompt is over 100,000 tokens pays $0.50 and $2.50 instead. Through the Batch API the lower rates are $0.05 and $0.25.

How much does prompt caching save on Claude?

A cache read costs 0.1x the base input price on most models, 0.05x on Opus 5.5 and Sonnet 5.5, and 0.025x on Fable 5.1. Writing to the cache costs 1.25x the input price for a 5-minute cache and 2x for a 1-hour cache. On the current models the cached prefix must be at least 512 tokens.

Does Claude charge more for long prompts?

Not on Fable 5.1, Opus 5.5 or Sonnet 5.5: their 1M-token context window is billed at the standard rate. Haiku 5.5 is the exception: a request whose prompt is over 100,000 tokens pays 5 times the lower rates. The legacy Haiku 4.5 has a 200K-token context window.

Do newer Claude models use more tokens for the same text?

Yes. Anthropic says Claude 4.7 and later models use a newer tokenizer that produces about 30% more tokens for the same text, depending on the content. Sonnet 4.6, Haiku 4.5 and earlier models use the previous tokenizer, so compare costs per task, not only per token.

Is Claude Mythos the same model as Claude Fable?

No. Claude Mythos 5.1 and Mythos 5 are separate models with limited availability, open only to organizations verified through Anthropic's verification programs, such as the Cyber Verification Program. Their listed token prices match Fable 5.1 and Fable 5.

Does Claude's web search cost extra?

Yes. Web search costs $10 per 1,000 searches on the Claude API, plus standard token prices for the search results that enter the context. Web fetch has no extra charge: you pay only for the tokens of the fetched content.

Azure OpenAI Pricing (Oct 2026): GPT-6, Flex, PTU and Costs

scorpion4ik26-lang — Fri, 16 Oct 2026 09:05:53 +0000

I am the founder of PromptUnit. This post first appeared on the PromptUnit blog, where the prices are kept current.

Azure OpenAI and OpenAI's own API charge the same per-token list price for the same model, as long as you use Azure's Global Standard deployment. GPT-6.1 Sol, for example, costs $2.00 per million input tokens and $10.00 per million output tokens on both. What changes your bill is the deployment type you choose (Data Zone costs 10% more in US regions), whether you pay for provisioned throughput by the hour or reserve it, batch discounts, and the Azure services around the model: support, networking and monitoring.

The Azure prices below come from Microsoft's public Azure Retail Prices API (East US 2, USD, list prices). We used the API because the official Azure OpenAI pricing page loads its prices with JavaScript, and on October 12 it said its GPT-6 Sol and Luna prices were still being published. The OpenAI prices come from OpenAI's pricing page. We checked both on October 12, 2026. Microsoft now sells Azure OpenAI inside Microsoft Foundry, so you may see it called Foundry Models. Your own price can differ with an enterprise agreement, another region or another currency, so confirm in the Azure pricing calculator or with Microsoft before you commit.

Azure OpenAI pricing for GPT-6 and GPT-5.6

Standard pay-as-you-go prices per 1 million tokens, input / output, for prompts up to 272K input tokens. Longer prompts cost more on both platforms: GPT-6 Sol, for example, goes to $4.00 / $15.00.

Model	OpenAI direct	Azure Global Standard	Azure Data Zone (US regions)
GPT-6 Astra	$10.00 / $50.00	$10.00 / $50.00	$11.00 / $55.00
GPT-6.1 Sol	$2.00 / $10.00	$2.00 / $10.00	$2.20 / $11.00
GPT-6 Sol	$2.00 / $10.00	$2.00 / $10.00	$2.20 / $11.00
GPT-6 Luna	$0.10 / $0.50	$0.10 / $0.50	$0.11 / $0.55
GPT-5.6 Sol	$4.00 / $20.00	$4.00 / $20.00	$4.40 / $22.00
GPT-5.6 Terra	$2.00 / $12.00	$2.00 / $12.00	$2.20 / $13.20
GPT-5.6 Luna	$0.20 / $1.20	$0.20 / $1.20	$0.22 / $1.32

What the table shows:

Global Standard matches OpenAI's list price on every model above.
Data Zone costs 10% more than Global in every commercial US region in Microsoft's price list (the US Government regions have their own, higher prices). Outside the US it can cost 20% more: for the GPT-6 models in EU regions such as Sweden Central and West Europe (GPT-6 Sol is $2.40 / $12.00 there), and for GPT-5.5 and GPT-5.4 in Asia Pacific regions.
OpenAI calls GPT-5.6 Sol's price promotional and says it is available at least through November 21, 2026. Azure lists the same $4.00 / $20.00 today. Check both again after that date.
OpenAI's own models page suggests GPT-6 Astra for complex reasoning and coding, GPT-6.1 Sol to balance intelligence and cost, and GPT-6 Luna for cost-sensitive, high-volume work.

Flex and priority: half price or double

Both platforms sell the same models at a lower price for work that can wait (Flex) and at a higher price for faster answers (priority). Per 1 million tokens, input / output, prompts up to 272K tokens, from Microsoft's price list (East US 2) and OpenAI's pricing page, checked October 15, 2026:

Model	Standard (both)	Flex (OpenAI and Azure Global)	Priority on OpenAI ("Fast mode")	Priority on Azure Global
GPT-6 Astra	$10.00 / $50.00	$5.00 / $25.00	$20.00 / $100.00	Not listed
GPT-6.1 Sol	$2.00 / $10.00	$1.00 / $5.00	$4.00 / $20.00	Not listed
GPT-6 Sol	$2.00 / $10.00	$1.00 / $5.00	$4.00 / $20.00	$4.00 / $20.00
GPT-6 Luna	$0.10 / $0.50	$0.05 / $0.25	$0.20 / $1.00	Not listed
GPT-5.6 Sol	$4.00 / $20.00	$2.00 / $10.00	$8.00 / $40.00	$8.00 / $40.00
GPT-5.6 Terra	$2.00 / $12.00	$1.00 / $6.00	$4.00 / $24.00	$4.00 / $24.00
GPT-5.6 Luna	$0.20 / $1.20	$0.10 / $0.60	$0.40 / $2.40	$0.40 / $2.40

What the table shows:

Flex is exactly half the standard price on both platforms, and Azure lists it for Global deployments only. Microsoft's list has no Batch prices for these models, so on Azure, Flex is the half-price option for evaluations, enrichment and other background jobs.
Priority is exactly double on both where it is listed. Microsoft lists it for GPT-6 Sol and the GPT-5.6 models; on Data Zone it costs another 10%.
OpenAI renamed priority processing "Fast mode" on July 30, 2026. It also sells an Ultrafast tier for GPT-6 Astra and GPT-6.1 Sol at six times the standard price ($60.00 / $300.00 and $12.00 / $60.00); Microsoft's list has nothing like it.
Cached input follows the same rule: GPT-6.1 Sol's cache reads cost $0.05 per million tokens on Flex against $0.10 on standard.

Cached input and cache writes

On the GPT-6 and GPT-5.6 models, prompt caching is billed in two parts: a cache write when a prompt prefix is first stored, and a much lower cached-input price when a later request reuses it. Azure Global Standard lists the same cache prices as OpenAI for these models, per 1 million tokens:

Model	Input	Cache write	Cached input
GPT-6 Astra	$10.00	$12.50	$1.00
GPT-6.1 Sol	$2.00	$2.50	$0.10
GPT-6 Sol	$2.00	$2.50	$0.20
GPT-6 Luna	$0.10	$0.125	$0.01
GPT-5.6 Sol	$4.00	$5.00	$0.40
GPT-5.6 Terra	$2.00	$2.50	$0.20
GPT-5.6 Luna	$0.20	$0.25	$0.02

OpenAI's prompt caching guide gives the rule behind these numbers for GPT-5.6 and later: a write costs 1.25 times the normal input price, a read costs 0.1 times (0.05 times on GPT-6.1 Sol), and only prefixes of at least 1,024 tokens are cached. A prefix written once and then read nine times costs 2.15 times its normal input price, instead of 10 times without caching. Our prompt caching guide covers how to structure prompts so the cache gets used.

Older models: GPT-5.5, GPT-5.4, GPT-5 and GPT-4o

If you still run one of these models, here are their prices. OpenAI direct and Azure Global Standard charge the same, so they share a column:

Model	OpenAI direct and Azure Global Standard	Azure Data Zone (US regions)	Azure Global Batch
GPT-5.5	$5.00 / $30.00	$5.50 / $33.00	$2.50 / $15.00
GPT-5.4	$2.50 / $15.00	$2.75 / $16.50	$1.25 / $7.50
GPT-5.4 mini	$0.75 / $4.50	$0.825 / $4.95	$0.375 / $2.25
GPT-5	$1.25 / $10.00	$1.375 / $11.00	$0.625 / $5.00
GPT-5 mini	$0.25 / $2.00	$0.275 / $2.20	$0.125 / $1.00
GPT-4o	$2.50 / $10.00	$2.75 / $11.00	$1.25 / $5.00
GPT-4o mini	$0.15 / $0.60	$0.165 / $0.66	$0.075 / $0.30

GPT-5.5 and GPT-5.4 prices are for prompts under 272K tokens. Global Batch is half the Global Standard price on Azure, and OpenAI's Batch API gives the same 50% off these models. Microsoft's price list still has no Batch prices for the GPT-6 and GPT-5.6 models (checked October 15), but it now lists Flex at half price for them (see the Flex section above). On OpenAI, Batch and Flex are both half price, for example $1.00 / $5.00 for GPT-6 Sol.

The deployment types, in plain words

Microsoft's deployment types guide lists the options. The short version:

Deployment type	Where your data is processed	How you pay	Good for
Global Standard	Any Azure region	Per token	Most workloads: lowest price, new models first
Data Zone Standard	Inside the US, EU or APAC data zone	Per token	Teams that must keep processing inside a zone
Standard (regional)	Inside one Azure geography	Per token	Geography rules, low volume
Provisioned (PTU)	Global, Data Zone or regional	Per PTU per hour, or a 1-month or 1-year reservation	Steady high volume, steadier latency
Batch	Global or Data Zone	Per token at 50% off, 24-hour target	Large jobs that can wait

Microsoft's own advice is to start with Global Standard and move to another type only for a specific reason: data residency, reserved throughput or batch jobs. Global Standard also offers Flex processing for work that can wait and priority processing for faster answers, each billed per token at its own rate.

Azure OpenAI pricing calculator: monthly costs at three volumes

Put in your own numbers below: the calculator prices a month of tokens on each Azure deployment type and on OpenAI direct.

There is an interactive Azure OpenAI cost calculator (model, deployment type, monthly tokens, cached share) in the original version of this post.
Microsoft offers an official Azure pricing calculator for whole setups. For the model itself the arithmetic is short:

monthly cost = (input tokens ÷ 1,000,000 × input price) + (output tokens ÷ 1,000,000 × output price)

The table applies that formula at Global Standard prices, which are the same as OpenAI direct, to three monthly volumes with five input tokens for every output token:

Tokens per month (input + output)	GPT-6 Luna	GPT-6.1 Sol	GPT-6 Astra
5 million + 1 million	$1.00	$20.00	$100.00
50 million + 10 million	$10.00	$200.00	$1,000.00
500 million + 100 million	$100.00	$2,000.00	$10,000.00

On Data Zone in a US region, add 10% to every cell, so GPT-6.1 Sol at the middle volume becomes $220.00. On Flex, halve every cell: the same volume costs $100.00. For the GPT-6 models on Data Zone in the EU regions above, add 20% ($240.00).

Caching lowers the input side. Take the middle volume on GPT-6.1 Sol: if 30 million of the 50 million input tokens are cache reads and 1 million are cache writes, input costs $38.00 for the 19 million uncached tokens, $2.50 for the writes and $3.00 for the reads. That is $43.50 instead of $100.00, and the month comes to $143.50 instead of $200.00. Output costs 5 times as much as input on GPT-6.1 Sol, so long answers move the bill as much as long prompts. Use the token counts from your own usage dashboard.

Provisioned throughput (PTU): hourly or reserved

With provisioned throughput you pay for reserved capacity whether you use it or not. Microsoft bills it per PTU per hour, or at a lower rate with a 1-month or 1-year Azure reservation. List prices in East US 2 on October 12, 2026:

Deployment type	Hourly, per PTU	1-month reservation, per PTU	1-year reservation, per PTU	Minimum PTUs for GPT-6 Astra, GPT-6.1 Sol, GPT-5.6
Global Provisioned	$1.00	$260	$2,652	15
Data Zone Provisioned	$1.10	$286	$2,916	15
Regional Provisioned	$2.00	$286	$2,916	50

What 15 PTUs, the Global minimum, cost for one month:

How you pay	Cost for 15 PTUs
Hourly, all 730 hours of an average month	$10,950
1-month reservation	$3,900
1-year reservation	$3,315 a month ($39,780 a year)

For a deployment that runs all month, the hourly rate costs about 2.8 times a monthly reservation. Microsoft's PTU billing guide says hourly billing suits short-term use such as benchmarking, and that production deployments should use reservations. It also warns that a reservation does not guarantee capacity, so create the deployment first and buy the reservation after. Other regions cost more: in Sweden Central, Data Zone Provisioned is $1.20 per PTU per hour.

Is PTU worth it? At the yearly rate, 15 PTUs cost $3,315 a month. The same money buys about 830 million input and 165 million output tokens on GPT-6.1 Sol at Global Standard prices. PTU makes sense when steady traffic would cost more than that on pay-as-you-go. Throughput per PTU differs by model (Microsoft lists GPT-6.1 Sol at 3,000 input tokens per minute per PTU and GPT-6 Astra at 600), so size it with Microsoft's PTU sizing guide. PTU also gives guaranteed throughput and steadier latency, which Microsoft says best-effort standard deployments do not. For spiky or growing traffic, per-token pricing usually fits better.

Data residency costs extra on both platforms

If your data must stay in the US or the EU, budget for it on either platform when you use recent models:

Azure: Data Zone Standard is 10% over Global in US regions, and 20% over Global for the GPT-6 models in the EU regions we checked.
OpenAI: its pricing page says regional processing (data residency) endpoints cost 10% more for models released on or after March 5, 2026, and FedRAMP endpoints also cost 10% more. The GPT-6 Sol, GPT-6.1 Sol and GPT-6 Luna model pages each say regional processing adds a 10% premium where available.

So for GPT-6 models with EU residency, OpenAI's list uplift (10%) is lower than Azure's EU Data Zone uplift (20%). Check the models and regions you need, and count only the options that meet your rule.

What else changes the bill

The model price is only part of a production bill. These Azure items have no direct equivalent on OpenAI's API, so price them for your own setup:

Support. Production support on Azure comes from a paid Azure support plan. Microsoft lists Developer at $29 a month for trial and non-production use, Standard at $100 a month for production workloads and Professional Direct at $1,000 a month. Compare it with the support you get from OpenAI at your tier.
Data leaving Azure. Azure bills outbound data transfer per GB after the first 100 GB a month, which is free. Inbound data is free. If your app runs on AWS, Google Cloud or your own servers, every response travels out of Azure and counts.
Private networking. Private endpoints use Azure Private Link, billed per hour and per GB processed. Regulated teams often need it.
Logging. Azure Monitor and Log Analytics bill by the GB ingested and retained.

If you already run on Azure, several of these are costs you pay anyway. If you do not, add them to the comparison. Our Claude on AWS Bedrock vs Anthropic API comparison looks at the same question for another cloud.

When Azure wins, and when it is the only option

You already run on Azure and have credits or a spend commitment. Ask your Microsoft account team whether Azure OpenAI usage counts toward it.
You must keep data in a region or zone and need Azure's options. Data Zone and Regional deployments exist for that. For models released since March 5, 2026, Azure's US uplift matches OpenAI's 10%. For GPT-6 models in the EU, Azure's Data Zone costs more.
A compliance requirement decides it. Microsoft lists the certifications that cover Azure OpenAI on its compliance pages, and OpenAI lists its own on its security pages. Check both against your requirement (HIPAA, FedRAMP, SOC 2 and so on) before you compare prices. If only one of them qualifies, the price comparison no longer matters.
You can wait for new models. New models launch on Global Standard first. Microsoft says Data Zone types follow and geography-based types come last, with no guaranteed date, so a regional deployment may wait longer for a new model.

How to choose

Four questions decide it for most teams:

Do you already run on Azure? If yes, Azure OpenAI is usually simpler: your networking, monitoring and access controls exist, and Global Standard costs the same as OpenAI. If not, OpenAI direct has fewer extra line items.
Must data stay in a region or zone? If yes, budget 10% more for recent models on either platform, and 20% for GPT-6 models on Azure Data Zone in the EU.
Is your traffic steady and high? Compare a PTU reservation with pay-as-you-go using your own numbers, not the hourly PTU rate.
Can some work wait 24 hours? Batch is half price on OpenAI, and on Azure for GPT-5.5 and older models. Our guide to the Batch API's 50% discount covers which work fits.

Cut the bill on either platform

Choosing Azure or OpenAI changes the per-token price by 20% at most in the tables above. The model you pick changes it far more: GPT-6 Astra input costs $10.00 per million tokens and GPT-6 Luna costs $0.10, which is 100 times less. Many requests do not need the most expensive model. Our guides on model routing and cutting an OpenAI bill cover smaller models, caching, output limits and batch work. To compare another provider's prices, see our Claude API pricing guide.

PromptUnit makes that choice for each request. You change two settings in your app: the API base URL, which you point at PromptUnit, and your PromptUnit key, which you add as a header. Your own provider key stays. Each request is checked, and when a cheaper model is just as good for that request, PromptUnit uses it; otherwise the request goes to the model you asked for. It works with your OpenAI, Anthropic, Google, Groq and DeepSeek keys, and with your own OpenRouter key. It is free until it has saved you money, then it takes 20% of what it saves. If it saves nothing, you pay nothing. Start free.

PromptUnit does not connect to Azure OpenAI deployments directly today. OpenRouter can route to your own Azure deployment with its bring-your-own-key feature, and PromptUnit works with your OpenRouter key, but we have not tested the two together. If you need Azure OpenAI, email igal@promptunit.ai and tell us how you would use it.

FAQ

How much does Azure OpenAI cost?

On a Global Standard deployment you pay per token, at the same list price as OpenAI's own API. For example, GPT-6.1 Sol is $2.00 per million input tokens and $10.00 per million output tokens on both, and GPT-6 Luna is $0.10 and $0.50, checked October 15, 2026. Data Zone deployments cost 10% more in US regions, and provisioned throughput starts at $1.00 per PTU per hour.

Is Azure OpenAI cheaper than OpenAI?

Not on the per-token list price: Global Standard matches OpenAI. Azure can work out cheaper if Azure credits or a spend commitment cover it, or if a provisioned throughput reservation fits a steady high volume. Keeping data in a region costs extra on both: Azure Data Zone is 10% over Global in US regions and 20% for the GPT-6 models in the EU regions we checked, while OpenAI adds 10% on data residency endpoints for models released on or after March 5, 2026.

Does Azure OpenAI have a cheaper Flex tier?

Yes. Microsoft's price list now has Flex prices for Global deployments of the GPT-6 and GPT-5.6 models at half the Global Standard price, the same as OpenAI's Flex: GPT-6.1 Sol is $1.00 per million input tokens and $5.00 per million output tokens, GPT-6 Luna $0.05 and $0.25, checked October 15, 2026. Flex suits work that can wait. Microsoft's list has no Batch prices for these models.

Is there an Azure OpenAI pricing calculator?

Microsoft has an official Azure pricing calculator for whole setups. For the model itself the arithmetic is short: input tokens divided by 1,000,000 times the input price, plus output tokens divided by 1,000,000 times the output price. This page has a table of monthly costs for GPT-6 Luna, GPT-6.1 Sol and GPT-6 Astra at three volumes.

What does an Azure OpenAI PTU cost?

In East US 2 on October 12, 2026, Global Provisioned was $1.00 per PTU per hour, $260 per PTU for a 1-month reservation and $2,652 per PTU for a 1-year reservation. GPT-6 Astra, GPT-6.1 Sol and the GPT-5.6 models need at least 15 PTUs per Global or Data Zone deployment. For 15 PTUs that is $10,950 for a 730-hour month at the hourly rate, $3,900 with a monthly reservation and $3,315 a month with a yearly one.

Does OpenAI charge extra for data residency too?

Yes. OpenAI's pricing page says regional processing (data residency) endpoints cost 10% more for models released on or after March 5, 2026, and that FedRAMP endpoints also cost 10% more. So for recent models, keeping data in a region costs extra on both platforms.

Does PromptUnit work with Azure OpenAI?

Not directly. PromptUnit works with your own OpenAI, Anthropic, Google, Groq and DeepSeek keys, and with your own OpenRouter key. OpenRouter can route to your own Azure deployment through its bring-your-own-key feature, but we have not tested that combination. If you need Azure OpenAI, email igal@promptunit.ai and tell us how you would use it.