Mistral Medium 3.5 is Mistral's best model for writing — it scores 84/100 vs 72/100 for Mistral Large 2, at $1.5/1M input tokens. Across all providers, Claude Fable 5.1 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 Medium 3.5 is the strongest answer here for mistral model for writing — pick it when quality of output matters more than the $1.50/1M/1M input you pay for it.
Codestral 25.01 handles the same job for about 60% less per token. Start here and only move up if the output is not good enough.
Mistral Small 3.1 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 Medium 3.5 leads Mistral's lineup for writing at 84/100 ($1.5/1M input, 256K context).
Mistral Small 3.1 is the value pick at $0.1/1M input with a writing score of 66/100.
Claude Fable 5.1 (Anthropic) is the overall writing leader at 98/100 if provider choice is open.
Choose Mistral Medium 3.5 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 Fable 5.1 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 / Balanced / Aug 6, 2026
Best self-hostable multimodal model — European, dense, MIT-licensed.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
API price-performance is all that matters — DeepSeek V4-Pro is stronger and cheaper hosted.
Where the mistral model for writing recommendation shifts once you weigh price or latency differently.
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 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 |
| Codestral 25.01Mistral | $0.90/1M | $2.70/1M | $14 | 256k tokens | Very fast | 88 | 38 | 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.
The default answer for mistral model for writing — 91/100 on the coding axis, and the model we would start with unless the price below rules it out.
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.
Balanced enterprise model with consistent reasoning, good speed, and a dependable middle-ground — especially for European teams with data residency requirements.
You want best-in-class performance for any specific use case — the frontier leaders win.
A dependable generalist — especially relevant for EU teams that need data processed inside Europe.
Full pricing, benchmark table and release notes on the Mistral Large 2 page.
The fastest model in this shortlist for mistral model for writing. Pick it when turnaround is what your readers or users notice.
Ultra-cheap multimodal model for massive-volume, low-complexity pipelines. Full Mistral Small 3.1 review →
The value option for mistral model for writing: about 60% less per token than Mistral Medium 3.5, at 88/100 on coding. Worth starting here and moving up only if the output disappoints.
Best budget-focused coding specialist for high-volume developer teams. Full Codestral 25.01 review →
UseRightAI recommendations are based on practical decision factors people actually feel in day-to-day use.
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Mistral Medium 3.5 — it scores 84/100 on writing in this directory, ahead of Mistral Large 2 at 72/100. Best self-hostable multimodal model — European, dense, MIT-licensed.
Not overall. Claude Fable 5.1 (Anthropic) leads the directory for writing at 98/100 vs Mistral Medium 3.5's 84/100. Mistral Medium 3.5 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 Medium 3.5 for the tasks where quality matters most.
$1.5/1M input tokens and $7.5/1M output tokens via the API, or through Le Chat Pro at $14.99/mo for chat use. Context window: 256K tokens. On a moderate month — 10M input and 2M output tokens — that works out to about $30.00, against $1.60 for Mistral Small 3.1.
Trails GPT-5.6, Opus-class, and Gemini frontier models on complex multi-step reasoning; sparse published benchmark disclosure. 256K context is a quarter of the 1M frontier norm, and $7.50/1M output is dear for the tier. Concretely, avoid it if API price-performance is all that matters — DeepSeek V4-Pro is stronger and cheaper hosted. If none of that is negotiable, Claude Fable 5.1 (Anthropic) is the cross-provider leader at 98/100.
coding at 77.6% SWE-bench Verified — within ~2 points of Claude Sonnet 4.6 at roughly half the price, document Q&A and vision tasks from a single checkpoint with structured outputs, and EU-compliant self-hosted deployments — 128B dense is far easier to run than trillion-parameter MoE rivals. Its 256K-token context window is the practical limit on how much you can hand it in one go.
Mistral Medium 3.5 scores 84/100 on writing against 66/100 for Mistral Small 3.1, at 15x 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.