Mistral Large 4 is Mistral's best model for writing — it scores 85/100 vs 84/100 for Mistral Medium 3.5, at $0.68/1M input tokens. Across all providers, Claude Sonnet 5.5 still leads writing at 98/100 — worth considering if you're not committed to Mistral.
The safest mistral model for writing default, the cheaper option worth trying first, and the specialist pick — before you read the detail below.
Mistral Large 4 is the strongest answer here for mistral model for writing — pick it when quality of output matters more than the $0.68/1M/1M input you pay for it.
Mistral Small 3.1 handles the same job for about 86% less per token. Start here and only move up if the output is not good enough.
Mistral Medium 3.5 is the fastest of these for mistral model for writing — worth it when latency is what the reader notices, not the last few points of reasoning depth.
Mistral Large 4 leads Mistral's lineup for writing at 85/100 ($0.68/1M input, 524K context).
Mistral Small 3.1 is the value pick at $0.1/1M input with a writing score of 66/100.
Claude Sonnet 5.5 (Anthropic) is the overall writing leader at 98/100 if provider choice is open.
Choose Mistral Large 4 when writing quality is the priority and you're staying on Mistral.
Choose Mistral Small 3.1 when token volume matters more than peak quality.
Teams open to other providers should also evaluate Claude Sonnet 5.5 before committing.
Switch the scoring lens to see whether the mistral model for writing answer changes when cost, speed, or long-document depth leads the decision.
Mistral / Budget / Oct 10, 2026
Mistral's open-weight flagship, cheap but still in preview.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
You need peak capability today — independent results so far place it mid-table — or you need the weights now.
Where the mistral model for writing recommendation shifts once you weigh price or latency differently.
Mistral's open-weight flagship, cheap but still in preview.
Best self-hostable multimodal model — European, dense, MIT-licensed.
Best balanced generalist for EU teams with data residency needs.
Ultra-cheap multimodal model for massive-volume, low-complexity pipelines.
Best budget-focused coding specialist for high-volume developer teams.
List prices and published scores — the numbers this page's pick is built from.
| Model | Input | Output | Est. month | Context | Speed | Coding | Writing | Research |
|---|---|---|---|---|---|---|---|---|
| Mistral Large 4Mistral | $0.68/1M | $2.09/1M | $11 | 524k tokens | Balanced | 83 | 85 | 83 |
| Mistral Medium 3.5Mistral | $1.50/1M | $7.50/1M | $30 | 256k tokens | Balanced | 91 | 84 | 82 |
| Mistral Large 2Mistral | $3.00/1M | $9.00/1M | $48 | 128k tokens | Balanced | 72 | 72 | 71 |
| Mistral Small 3.1Mistral | $0.10/1M | $0.30/1M | $1.60 | 128k tokens | Very fast | 55 | 66 | 52 |
Scores out of 100 — how we evaluate models. “Est. month” is 10M in / 2M out at list price: a ceiling, no discounts.
Why each one is on the shortlist for mistral model for writing, what it is genuinely good at, and where we would steer you away from it.
Ranked first here for mistral model for writing: 83/100 on coding, with the widest margin of anything in this line-up.
Mistral's October 6, 2026 flagship, in public preview: a natively multimodal mixture-of-experts model with about 1 trillion total parameters, open weights promised for later in October, at $0.68/$2.09 per 1M.
You need peak capability today — independent results so far place it mid-table — or you need the weights now.
Promising, not yet proven. The price is low and the open weights matter for teams that must self-host, but early independent scoring puts it in the middle of the pack. Wait for the weights and more third-party results before building on it.
Full pricing, benchmark table and release notes on the Mistral Large 4 page.
The fastest model in this shortlist for mistral model for writing. Pick it when turnaround is what your readers or users notice.
A 128B dense open-weight multimodal model handling reasoning, coding, and vision in one set of weights — frontier-adjacent coding at mid-tier prices, self-hostable under a modified MIT license.
API price-performance is all that matters — DeepSeek V4-Pro is stronger and cheaper hosted.
The best open-weights model you can realistically self-host. DeepSeek V4 beats it on benchmarks and price via API, but at 128B dense with vision, Medium 3.5 is what you can actually run on your own hardware with EU data residency.
Full pricing, benchmark table and release notes on the Mistral Medium 3.5 page.
Rounds out the shortlist for mistral model for writing at 72/100 on coding.
Best balanced generalist for EU teams with data residency needs. Full Mistral Large 2 review →
The cost-conscious pick for mistral model for writing, about 86% less per token than Mistral Large 4 than the top choice while holding 55/100 on coding.
Ultra-cheap multimodal model for massive-volume, low-complexity pipelines. Full Mistral Small 3.1 review →
UseRightAI recommendations are based on practical decision factors people actually feel in day-to-day use.
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Mistral Large 4 — it scores 85/100 on writing in this directory, ahead of Mistral Medium 3.5 at 84/100. Mistral's open-weight flagship, cheap but still in preview.
Not overall. Claude Sonnet 5.5 (Anthropic) leads the directory for writing at 98/100 vs Mistral Large 4's 85/100. Mistral Large 4 is the best pick if you're staying within Mistral's ecosystem.
Mistral Small 3.1 at $0.1/1M input tokens (writing score: 66/100). Use it for volume work and reserve Mistral Large 4 for the tasks where quality matters most.
$0.68/1M input tokens and $2.09/1M output tokens via the API. Context window: 524K tokens. On a moderate month — 10M input and 2M output tokens — that works out to about $10.98, against $1.60 for Mistral Small 3.1.
Still a preview: the weights were not downloadable as of October 10, 2026. All benchmark claims so far are Mistral's own; Vals AI ranks it 32nd of 44 on its index. Concretely, avoid it if you need peak capability today — independent results so far place it mid-table — or you need the weights now. If none of that is negotiable, Claude Sonnet 5.5 (Anthropic) is the cross-provider leader at 98/100.
teams that need a European provider or plan to self-host once the weights ship, finance and cybersecurity analysis, the domains Mistral highlights, and visual grounding over charts, diagrams and screenshots. Its 524K-token context window is the practical limit on how much you can hand it in one go.
Mistral Large 4 scores 85/100 on writing against 66/100 for Mistral Small 3.1, at 7x the input price. That premium is worth it on work where a wrong answer costs real time or money, and hard to justify on high-volume, low-stakes calls. Most teams run both and route by task rather than picking one.