What one chat reply costs across 330 AI models (Nov 2026)

When people compare LLMs, they usually compare per-million-token prices. Those numbers are accurate, but they are awkward to reason about when what you actually do is send a message and read an answer. I wanted a more concrete question: what does one ordinary chat reply cost, and how much does that change from model to model?

I built a small site that lists models with prices and an estimated cost per reply, so I had the data on hand. This post walks through how the math works and what the spread looks like as of mid-November 2026.

From per-1M prices to a per-reply cost

Every model is priced in dollars per 1 million input tokens and per 1 million output tokens. A single reply costs:

cost = (input_tokens / 1,000,000) * input_price
     + (output_tokens / 1,000,000) * output_price

Two details matter in practice:

1. Input includes history. In a chat, each new message sends your text plus the earlier messages, so input grows as a conversation goes on.
2. Output usually costs several times more than input. On the models below, output is 2.5x to 5x the input price. Long answers are where the money goes.

For the estimates on my site I use a fixed "typical reply": about 300 words in and 500 words out. Real replies are billed by their own token counts, so a short question with a short answer costs less and a long conversation costs more. The typical reply is just a way to compare models on equal footing.

The spread, in a table

These are prices from OpenRouter's public model list, synced on November 14, 2026. The last column is the site's estimate of credits per typical reply, where one credit is about $0.01 at pack prices.

A few things stand out.

The spread is large. Output on Claude Fable 5.2 is $40 per million tokens, against $0.50 for GPT-6 Luna. That is an 80x difference in output price. In reply terms it is about 9 credits versus about 1, roughly nine cents versus one cent.

There is a floor. The ERNIE row costs more per token than Luna or Inkling, yet it still shows about 1 credit. That is because each reply costs at least 1 credit, so below a certain price the per-token differences stop showing up on the bill. For small models, the question is no longer "which is cheapest" but "which is good enough".

Doubling the price roughly doubles the reply cost. Opus 5.5 ($4 / $20) is half of Fable 5.2 ($8 / $40), and the estimate goes from about 9 credits to about 5. Anthropic's own guidance, as quoted on the Fable 5.2 vs Opus 5.5 comparison, is to start most work with Opus 5.5 and move up to Fable 5.2 for more demanding reasoning and long-horizon agent work, or when your own evaluations at higher effort still fall short. That is a sensible rule for any pair of models: start with the cheaper one, and move up when you can point to a failure.

Prices move. Gemini 4 Carbon is listed at $2 / $10 until November 30, 2026 and $4 / $20 from December 1, per Google's pricing page, as summarized on the DeepSeek V4.1 Flash vs Gemini 4 Carbon page. Whether OpenRouter follows that change was not confirmed when I last checked. If you budget from a table like the one above, put a date on it.

When a cheaper model is good enough

I have no benchmark scores to offer, and I would rather not invent any. As a rule of thumb, the cheap end is often fine for:

• Rewriting, summarizing, or reformatting text you already have
• Short factual questions and quick explanations
• Drafting boilerplate such as email subjects, commit messages, or docstrings
• First-pass code questions where you will check the answer anyway

The pricier models earn their cost on work where a wrong answer is expensive for you: long multi-step reasoning, large refactors, or agent loops that run for a while. A practical habit: send the same prompt to a cheap and an expensive model. If you cannot tell the difference, you have your answer.

Conversation length is another lever: history is re-sent as input, so a long thread on an expensive model gets costly. A fresh chat per topic is the cheapest optimization there is.

The site

The site is AI Model Buffet. You pick from 331 text models and chat with all of them from one credit balance. Each reply is charged by its real token cost, with the service fee included and a minimum of 1 credit. A new account gets 5 free credits once, valid for 7 days, and paid plans start at $9.90 per month (1,200 credits a month). There are also one-time credit packs.

The conversation is kept in your browser; the server stores only the model, credits, token counts and cost of each reply, not the text. It is an independent service and is not affiliated with or endorsed by OpenRouter or any model maker. Replies are AI-generated and can be wrong, like any chatbot.

Takeaways

• Per-reply cost is input tokens times the input price plus output tokens times the output price, and output usually dominates.
• Between the cheapest and priciest listed models, the gap is around 80x on output price, and about 9x in typical credits per reply.
• Many small models hit a billing floor, so compare quality, not just price, once you are down there.

If you have a workload where a cheap model surprised you, or an expensive one clearly paid for itself, I would like to hear about it in the comments.