Mistral Large 4 vs Claude Opus 5.5: open weights or top closed model?

The short answer: Opus for hardest tasks, Mistral for cost and control

Choose Claude Opus 5.5 when task success matters more than price: published scores put it well ahead. Choose Mistral Large 4 when you need to self-host for data control, or run high volumes where $0.70 input and $2.10 output per million tokens changes the budget compared with Opus's $4 and $20.

Scope and evidence

Task: choosing a model for coding agents and long-document work. Mistral facts come from Mistral's launch post, documentation and the Hugging Face model card; Opus facts from Anthropic's Opus 5.5 overview and pricing page. Pages read on October 30 and 31, 2026.

Benchmark figures come from different publishers, so treat cross-source comparisons as indicative. No hands-on test of Mistral Large 4 or Opus by AppFor.ai sits behind this page.

Compare the same criteria

Each line gives the Mistral figure, the Opus figure and what the gap means in practice.

• API price per million tokens. Mistral Large 4: $0.70 input, $0.07 cached input, $2.10 output. Opus 5.5: $4 input, $20 output, 50% off on Batch. What this means: Mistral is roughly 6 to 10 times cheaper per token.
• Weights and licence. Mistral: open weights under the Mistral Ecosystem Open-Weight License; Model-as-a-Service providers need a separate licence. Opus: closed, API and Claude apps only. What this means: only Mistral can run on your hardware.
• Context. Mistral: 1M tokens, text and image in. Opus: 1M context, 128K output. What this means: both handle very long inputs.
• Intelligence Index v5. Mistral: 26 per its model card. Opus: 58 in Google DeepMind's comparison table. What this means: a large gap in general capability.
• Terminal-Bench 4.0. Mistral: 41% per Mistral. Opus: 59.6% in Google DeepMind's table. What this means: Opus completes clearly more terminal tasks.
• Hardware for self-hosting. Mistral: about 1T total and 52B active parameters; the reference vLLM setup uses eight GPUs. What this means: self-hosting needs a multi-GPU server.

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Which fits your real work?

A regulated company that cannot send code to a third-party API. Mistral Large 4 fits, since the weights run on its own servers.

A team running a coding agent on difficult multi-step issues. Opus 5.5 fits on the published scores.

A product summarising millions of documents a month. Mistral fits on price, provided quality holds on a sample.

Cost of getting the work done

API: 2 million input and 200,000 output tokens cost about $1.82 on Mistral Large 4 and $12 on Opus 5.5 before caching or batch discounts.

Self-hosting Mistral replaces token fees with GPU costs; Opus is also included in Claude Pro at $20 a month for app use.

Try both on the same small task

Suggested check: run one real issue through both APIs with the same files and compare result and tokens.

• The patch makes the failing test pass.
• No unrelated files change.
• The explanation matches the real cause.
• Record tokens and cost per run for each model.

Decision checklist

Use the lines that match your situation. Our Mistral Large 4 and Claude Opus 5.5 profiles cover each model in more depth.

• If data must stay on your servers, choose Mistral Large 4.
• If the hardest tasks must succeed first time, choose Opus 5.5.
• If volume drives cost, price your workload on Mistral first.
• If you sell model access, read Mistral's licence condition.
• If you lack GPUs, test Mistral through its API before buying hardware.

Go a little further

Related reading

• Mistral Large 4 profile →
• Claude Opus 5.5 profile →