Comparison · Mistral and OpenAI
Mistral Small 4 vs GPT-6 Luna
Listed API prices of Mistral Small 4 and GPT-6 Luna turned into the cost of the same three standard tasks and what each provider’s API documentation says about features that break on a switch. Output quality, speed and answer length are not compared.
Calculated impact cost per task and per month
For an L2 task (deep analysis over a 50,000-token document, 3 steps), Mistral Small 4 costs $0.026 and GPT-6 Luna $0.017 at the prices listed in the United States on , so Mistral Small 4 is 47.4 % more than GPT-6 Luna, counting visible output only, without cache discounts or hidden reasoning.
| Task | Mistral Small 4, per task | GPT-6 Luna, per task | Mistral Small 4, per month | GPT-6 Luna, per month | Mistral Small 4 vs GPT-6 Luna, per task |
|---|---|---|---|---|---|
| L1Micro-task (classification or strict JSON extraction) | $0.0003per L1 task | $0.0003per L1 task | $5.04per month | $3.65per month | +38.0 % |
| L2Deep analysis over a 50,000-token document | $0.026per L2 task | $0.017per L2 task | $374.49per month | $254.04per month | +47.4 % |
| L3Agentic coding loop, 15 steps | $0.203per L3 task | $0.136per L3 task | $2,959.78per month | $1,986.33per month | +49.0 % |
Calculated Per month: 20 tasks an hour around the clock, 730 hours.
Prices USD per 1M tokens
| Price | Mistral Small 4 | GPT-6 Luna |
|---|---|---|
| Input, per 1M tokens | $0.150 | $0.100 |
| Output, per 1M tokens | $0.600 | $0.500 |
| Price from | OpenRouter · source page (data) Published | Provider's price list · source page Published |
| Read | · the United States | · the United States |
| Context window | 262,144 tokens | 1,050,000 tokens |
What can I use it for? six common tasks, our data checks
Quality on your task: not measured by Measured Lab yet.
| Task | Mistral Small 4 | GPT-6 Luna |
|---|---|---|
| Answer customer messages | Fits on price and context | Fits on price and context |
| Pull data from invoices and documents with strict JSON and page images | Fits on price and context | Fits on price and context |
| Summarize documents and meetings | Fits on price and context | Fits on price and context |
| Translate content | Fits on price and context | Fits on price and context |
| Chat assistant on your website | Fits on price and context | Fits on price and context |
| Write and review code with tool calls | Fits on price and context | Fits on price and context |
| Tasks it fits | 6 of 6 | 6 of 6 |
Checks of our data for six common tasks: a published price, a context window and answer length for the task and, where the task needs them, strict JSON output, page images and tool calls; prices, cost a month and terms for each model on its model card. Compare models for your own task in the model picker.
What breaks when you switch Published provider documentation
Moving from Mistral to OpenAI: every feature that Mistral’s documentation lists as supported is also listed as supported by OpenAI.
Moving from OpenAI to Mistral, 3 of the 5 features may not carry over, by each provider’s documentation:
- Streamed tool arguments — OpenAI: yes; Mistral: not stated. An interface that shows arguments as they are written sees nothing until the whole call is ready.
- Reasoning with tools — OpenAI: yes; Mistral: not stated. Switching reasoning on can rule out some tool settings or output formats, or the other way round.
- Cache covers tool definitions — OpenAI: yes; Mistral: not stated. Where the cache does not cover tool definitions, a long tool list is paid as fresh input on every request.
| Feature of the API | Mistral | OpenAI |
|---|---|---|
| Strict JSON schemas | Yes | Yes |
| Parallel tool calls | Yes | Yes |
| Streamed tool arguments | Not stated | Yes |
| Reasoning with tools | Not stated | Yes |
| Cache covers tool definitions | Not stated | Yes |
What each provider’s own API documentation says, read ; “not stated” is not the same as “no”. Quotes and sources: what breaks when you switch AI APIs.