Neither wins outright: Mistral: Mistral Medium 3.5 (batch) is the pick when cost matters at scale, OpenAI: GPT-5.1-Codex-Max when you need to fit long inputs in one request.
| Spec | Mistral: Mistral Medium 3.5 (batch) | OpenAI: GPT-5.1-Codex-Max |
|---|---|---|
| Provider | Mistral AI | OpenAI |
| Input price (per 1M tokens) | $0.75 | $1.25 |
| Output price (per 1M tokens) | $3.75 | $10.00 |
| Blended price (3:1 input/output) | $1.50 | $3.44 |
| Cheaper than … of all models we track | 31% | 19% |
| Context window | 262K tokens (~393 pages) | 400K tokens (~600 pages) |
| Larger context than … of all models | 48% | 63% |
| Max output per response | 210K tokens (~157,300 words) | 128K tokens (~96,000 words) |
| Input types | text, image, file | text, image |
| Output types | text | text |
| Free variant | No | No |
| Listed since | 2026-04-30 | 2025-12-04 |
Monthly cost at list price for five common workloads. Token counts per unit are stated so you can scale them to your own traffic. A workload that does not fit a model's context window is marked rather than priced.
| Workload (per month) | Mistral: Mistral Medium 3.5 (batch) | OpenAI: GPT-5.1-Codex-Max | Difference |
|---|---|---|---|
| Customer-support chatbot 50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens) | $131 | $294 | Mistral: Mistral Medium 3.5 (batch) saves $163 |
| RAG search over documents 20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens) | $127 | $250 | Mistral: Mistral Medium 3.5 (batch) saves $123 |
| Coding / tool-using agent 2,000 tasks — each a multi-step task with tool calls and file context (60,000 in / 6,000 out tokens) | $135 | $270 | Mistral: Mistral Medium 3.5 (batch) saves $135 |
| Batch summarisation 10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens) | $82.50 | $160 | Mistral: Mistral Medium 3.5 (batch) saves $77.50 |
| Long-document analysis 500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens) | $41.25 | $72.50 | Mistral: Mistral Medium 3.5 (batch) saves $31.25 |
| Capability | Mistral: Mistral Medium 3.5 (batch) | OpenAI: GPT-5.1-Codex-Max | What it lets you do |
|---|---|---|---|
| Tool / function calling | ✓ Yes | ✓ Yes | call your APIs and run agent loops |
| Structured output (JSON schema) | ✓ Yes | ✓ Yes | return JSON that validates against your schema |
| Reasoning / thinking mode | ✓ Yes | ✓ Yes | spend extra tokens thinking before answering hard problems |
| Image input | ✓ Yes | ✓ Yes | read screenshots, charts and scanned pages |
| Audio input | — | — | take speech or audio directly |
| File / PDF input | ✓ Yes | — | accept documents without your own parsing step |
| Image output | — | — | generate images, not just text |
| Built-in web search | — | ✓ Yes | answer from live web results |
| Seed (reproducible sampling) | ✓ Yes | ✓ Yes | repeat a generation for tests and evals |
| Log-probabilities | — | — | read token confidence for classification and scoring |
From each model's published parameters and input/output types. “—” means not advertised, not proven absent.
Neither wins outright: Mistral: Mistral Medium 3.5 (batch) is the pick when cost matters at scale, OpenAI: GPT-5.1-Codex-Max when you need to fit long inputs in one request. In short: Mistral: Mistral Medium 3.5 (batch) when cost matters at scale, you need file / PDF input, you generate long outputs in one go, you want the newer model; OpenAI: GPT-5.1-Codex-Max when you need to fit long inputs in one request, you need built-in web search.
Mistral: Mistral Medium 3.5 (batch) is cheaper: $1.50 vs $3.44 per 1M tokens at a typical 3:1 input/output mix, 56% less. For 50,000 support conversations a month that is $131 against $294.
Mistral: Mistral Medium 3.5 (batch) costs $0.75 per 1M input tokens and $3.75 per 1M output tokens; OpenAI: GPT-5.1-Codex-Max costs $1.25 input and $10.00 output. Output tokens are billed separately, so long answers shift the gap.
OpenAI: GPT-5.1-Codex-Max: 400K tokens, about 600 pages, against 262K (about 393 pages) for Mistral: Mistral Medium 3.5 (batch).
Tool calling — Mistral: Mistral Medium 3.5 (batch): yes, OpenAI: GPT-5.1-Codex-Max: yes. JSON-schema structured output — Mistral: Mistral Medium 3.5 (batch): yes, OpenAI: GPT-5.1-Codex-Max: yes.
Yes, both accept image input.
No free variant is listed for either; both are pay-per-token.
Mistral: Mistral Medium 3.5 (batch) can write up to 210K tokens (about 157,300 words) per response; OpenAI: GPT-5.1-Codex-Max up to 128K (about 96,000 words).
Mistral: Mistral Medium 3.5 (batch) was listed on 2026-04-30; OpenAI: GPT-5.1-Codex-Max on 2025-12-04.
Mistral Medium 3.5 is a dense 128B instruction-following model from Mistral AI. It supports text and image inputs with text output, and is designed for agentic workflows, coding, and complex...
Full Mistral: Mistral Medium 3.5 (batch) specs →GPT-5.1-Codex-Max is OpenAI’s latest agentic coding model, designed for long-running, high-context software development tasks. It is based on an updated version of the 5.1 reasoning stack and trained on agentic...
Full OpenAI: GPT-5.1-Codex-Max specs →