DEV Community: neo xia

Why I Chose DeepSeek Over GPT-4 for a Free AI Conversation App

neo xia — Mon, 22 Jun 2026 06:43:39 +0000

I did not choose DeepSeek because I think GPT-4 is bad. I chose it because I was building a free app, and free apps teach you what actually matters pretty fast.

The question was simple: how do I keep sessions cheap enough that people can practice a lot without me lighting money on fire?

The answer pushed me toward DeepSeek-V3 (and later R1 for specific tasks).

The real constraint was volume

The app is a conversation practice tool. People come in to rehearse hard talks, not to admire the model.

A single practice session runs 8-15 turns. Each turn is roughly 300-600 tokens in, 100-300 out. Multiply that by five sessions a week per active user and the costs start compounding.

Here is what the math looked like when I was choosing (mid-2026 pricing):

Model	Input cost (per 1M tokens)	Output cost (per 1M tokens)	Cost per 10-turn session (est.)
GPT-4o	$2.50	$10.00	~$0.04-0.06
GPT-4 Turbo	$10.00	$30.00	~$0.12-0.18
DeepSeek-V3	$0.27	$1.10	~$0.004-0.007
DeepSeek-R1	$0.55	$2.19	~$0.008-0.012

At scale, the difference between $0.005 and $0.05 per session is the difference between running a free product and needing a paywall after three conversations. I wanted people to come back daily without hitting a wall.

What DeepSeek handled well

It stayed in character for 10-15 turns. It pushed back when the user got vague. It followed persona heuristics (numbered if/then rules in the system prompt) about as reliably as GPT-4o did for our use case.

For salary negotiation rehearsal, the model needs to say "that's not in the budget" and hold that position for three more turns while the user tries different approaches. DeepSeek-V3 did this. Not perfectly, but reliably enough that sessions felt real.

It also made the app easier to run as a free product. People can try, fail, reset, and try again without me worrying about per-session cost.

Where GPT-4 was still better

GPT-4 (and 4o) is smoother with nuanced emotional wording. When a conversation gets subtle, loaded with subtext, or requires picking up on implied meaning, GPT-4 catches more.

For the breakup text persona, GPT-4o noticed when a user's "kind" message was actually passive-aggressive. DeepSeek missed that about 20% more often in my informal testing across ~100 sessions.

But polish was not the main bottleneck for this product. The main bottleneck was getting people enough reps to build actual comfort with discomfort.

The tradeoff I actually cared about

Do I want one beautiful session, or ten useful ones?

For this app, ten useful ones. Every time.

So I took the cheaper model, put the engineering effort into the prompt architecture (persona seed, heuristics, mode wrapper, boundaries), and accepted that 85-90% quality at 10x the volume was a better product than 95% quality at 1x.

The model matters. The scaffolding around it matters more.

What I changed to make DeepSeek work

A few things made the choice viable:

Tighter system prompts. DeepSeek drifts more with long, loose instructions. Shorter seed, more numbered rules.
Lower temperature (0.55 for roleplay, 0.2 for scoring). Kept persona variation without character breaks.
Max reply length cap in the mode wrapper. DeepSeek's default is wordier than GPT-4o, so I had to constrain it explicitly.
Built retries into the flow. A bad response does not kill the session; the user gets a fresh turn.

The last one is underrated for any practice app. The experience should not feel fragile.

My actual takeaway

If you are building a free AI app, the best model is not always the smartest one. It is the one that lets people come back tomorrow.

Not bragging rights. Not benchmark charts. Whether the app stays affordable enough to be used like a tool instead of a demo.

For cosskill, DeepSeek made more sense. It let me build something people use five times a week instead of once and forget. Which is usually the whole game for a practice product anyway.

If you want to see the product, it is at cosskill.com.

I built an AI conversation simulator because I kept chickening out of real talks

neo xia — Mon, 01 Jun 2026 03:43:42 +0000

Last year I needed to ask for a raise. I knew my number, I'd read the guides, I had bullet points in my notes app. Then my manager said "let's chat about your goals for next quarter" and I said "sounds great, looking forward to it" and hung up. Never brought up money.

Same thing kept happening elsewhere. Coworker taking credit for my work, I said nothing. Relationship that should've ended months earlier, I kept postponing. I always knew what to say. I just couldn't say it with someone actually looking at me.

So I started building a thing to practice on. That thing became cosskill.

What it actually is

You pick a persona, tell it the situation in a sentence, and start talking. The persona doesn't help you. It holds position and pushes back. You practice not folding.

Think of it as a flight simulator for hard conversations. You rehearse until your opener comes out steady, then go do the real thing. 20 personas across five categories:

Operators (Musk, Jobs): first-principles thinking, harsh product feedback
Strategists (Trump, Buffett): treat everything as a deal or a bet
Relationship (Ex, Coworker): breakups, workplace friction, family money
Philosophy (Socrates, Aurelius, Confucius, Sun Tzu, four more): each tradition frames problems differently
Psychology (Rogers, Rosenberg, Ellis, Frankl, Kahneman, Jung): therapeutic frameworks on real situations

These aren't celebrity impressions. The Buffett persona won't hype your startup idea. It'll ask "what's the downside?" and keep asking until you have something concrete.

Tech stack

Next.js 16 on Cloudflare Workers. DeepSeek for inference. Cloudflare D1 (SQLite at edge) for the bits that need to persist. No user accounts, chat history lives in localStorage.

Monthly cost stays low enough that the free tier (10 messages/day) doesn't worry me.

Why I made these choices

DeepSeek instead of GPT-4/Claude. Each conversation is 10-30 messages. At GPT-4 pricing a free product bleeds money. DeepSeek gives maybe 90% of the quality for a fraction of the cost on this specific task, which is maintaining persona consistency across a back-and-forth.

No accounts. Every signup form is friction between "I need to practice this talk" and actually practicing it. If I add a login wall, some percentage of people close the tab and go back to rehearsing in the shower. I'd rather have them practice.

Cloudflare Workers instead of Vercel. D1 is genuinely good for this. One database at edge, no connection pooling, no separate DB service. DX is slightly worse for Next.js specifically but the deploy simplicity makes up for it.

Personas that resist instead of a chatbot that helps. A generic AI assistant will agree with you. That's the problem. You don't need agreement. You need someone saying "that's not in the budget" while you practice not conceding immediately. Each persona has hardcoded positions and pushback patterns. They're useful by being difficult.

What I actually learned building this

Prompting a persona to stay in character is a solved problem. The hard part was figuring out what "practice" means for conversations.

Scripts don't work because they sound robotic and shatter on contact with a real human. Free-form chatting doesn't work because there's no improvement loop. What actually works: have one sentence you want to say, say it to something that pushes back, adjust based on what happens, try again. The first two minutes of any hard conversation set the rest. So you practice those two minutes.

After a few runs, people say the real conversation feels less scary. Not because they memorized a script. Because they already heard the worst response and survived. "That's not in the budget" doesn't feel like a gut punch when you've heard it four times from an AI and practiced not caving.

Where it's at

Early. Traffic is growing organically. The pages that get the most hits are salary negotiation practice and breakup text help. Draw your own conclusions about what people actually struggle with.

Free tier handles most users. Pro ($9.90/month annual) is for people who want unlimited messages and custom personas.

Go try it

cosskill.com. No signup, just pick a persona and start. If you have a salary conversation coming up, try Buffett. Need to set a boundary with a coworker, try the Coworker persona. Want someone to tear your startup pitch apart, try Jobs.

Genuinely curious: what conversations do devs specifically need to practice that I haven't thought of? And what persona doesn't exist yet but should?

first time to here

neo xia — Mon, 01 Jun 2026 03:34:12 +0000