Model comparison
Compare GPT-5.6 Sol and Mistral Small 4 using the same provider-sourced text & reasoning rubric. No mystery score and no invented benchmark ranking.
Facts checked September 4, 2026
Set your usage. Your estimate updates as you type.
Example: 6,000 input tokens for 10 pages, plus a 500-token summary. Page lengths vary; adjust the numbers below.
One run sends your input to the model once and receives an answer. Tokens are pieces of text: input is what you send, output is the answer you receive.
Estimates exclude taxes, tools, cache storage/writes, free allowances and custom discounts. Image estimates cover output only, not prompt or reference-image charges. Quality modes differ by model. Unlisted settings are not treated as free.
| Model | Access | Estimated total (USD) |
|---|---|---|
| Mistral Small 4Mistral AI | Mistral AI | $0.0012 |
| GPT-5.6 SolOpenAI | OpenAI | $0.034 |
Quick take
OpenAI's flagship general model for difficult coding, analysis, and professional work, with a very large context window and a broad native tool set.
Budget with the long-context multiplier, cached-input rules, tool charges, and reasoning tokens—not only the headline input/output rate.
Mistral's lower-cost open model that combines normal instruction following, reasoning, coding, vision, and agent tools in one endpoint.
Sparse activation lowers inference work but does not make the full 119B checkpoint small. Size hardware around the actual quantization and context you plan to serve.
Compare the published facts
Values use each provider's own published units and limits. A blank means the provider did not publish a directly comparable value in the sources reviewed.
| Text & reasoning | GPT-5.6 Sol | Mistral Small 4 |
|---|---|---|
| Context windowMaximum combined prompt and working context documented by the provider. | 1.05M tokens | 256K tokens combined |
| Maximum outputProvider-published response limit, where available. | 128K tokens | Not separately published |
| Knowledge cutoffLatest reliable knowledge date explicitly published by the model provider. Search and connected tools can retrieve newer information but do not change the model's built-in cutoff. | February 16, 2026 | Not published |
| Input priceCurrent standard list price per million input tokens unless noted. | $4 / 1M | $0.15 / 1M |
| Output priceCurrent standard list price per million output tokens unless noted. | $20 / 1M | $0.60 / 1M |
| InputsMedia types accepted by the listed model endpoint. | Text, image | Text, image |
| Tools & agentsSelected native tools and agent-building capabilities, not an exhaustive list. | Functions, web/file search, code, computer, MCP | Functions, agents, built-in tools, structured and predicted outputs |
How to choose
Start with the job you need to complete, then validate cost, access, and policy details on your exact provider route.
OpenAI says API inputs and outputs are not used for model training by default. Default abuse-monitoring logs may be retained for up to 30 days; qualifying organizations can request other controls.
Provider and API links
Mistral's commercial terms exclude model training by default except when a customer opts in or uses designated Labs or preview models. Self-hosting keeps inference data under the operator's controls; hosted API retention is generally 30 days unless zero data retention is enabled.
Provider and API links
Frequently asked questions
GPT-5.6 Sol: OpenAI's flagship general model for difficult coding, analysis, and professional work, with a very large context window and a broad native tool set. Mistral Small 4: Mistral's lower-cost open model that combines normal instruction following, reasoning, coding, vision, and agent tools in one endpoint.
Consider GPT-5.6 Sol when your priority is Complex coding and repository work. Consider Mistral Small 4 when your priority is Cost-sensitive production assistants. Test both with your own data and provider route before committing.
No. This comparison aligns provider-published facts for the Text & reasoning category. It does not claim a universal winner or combine incompatible third-party benchmark scores.
