Mistral Large 4
Mistral Large 4Alternatives?
CheaperGPT-5.6 Lunamax×2.3-78%$0.18BetterGPT-6 Lunamax×2.1-90%$0.068Function calling only with none · Chat Completions+3
OpenKimi K3max+45%+191%$2.00Sampling parameters are fixed+3
CheaperClaude Haiku 5.5max+73%-90%$0.21Remove sampling parameters+5CheaperKimi K2.6unstatedOpen-4%-17%$0.95 / $4Context: 1M → 256KGPT-5.6 Lunamax×2.3-78%$0.18GPT-6 Lunamax×2.1-90%$0.068Function calling only with none · Chat Completions+3Claude Haiku 5.5max+73%-90%$0.21Remove sampling parameters+5Kimi K2.6unstatedOpen-4%-17%$0.95 / $4Context: 1M → 256K
Gemini 3.6 Flashhigh-18%-27%*$1.60GPT-6 Lunamax×2.1-90%$0.068Function calling only with none · Chat Completions+3GPT-5.6 Lunamax×2.3-78%$0.18Claude Haiku 5.5max+73%-90%$0.21Remove sampling parameters+5GPT-6.1 Solmax×3.7+94%$0.72Remove unsupported parameters+5GPT-6 Astralow×3.3+869%$0.82Monitoring can return HTTP 403+2Kimi K3maxOpen+45%+191%$2.00Sampling parameters are fixed+3
GLM 5.2maxOpen+9%+4%$1.47No image input+1GLM 5.3maxOpen+9%+4%$2.01No image input+5
DeepSeek V4 Pro 0813maxOpensame-4%$0.67No image input+6Kimi K2.6unstatedOpen-4%-17%$0.95 / $4Context: 1M → 256KMistral Medium 3.5highOpenn/a—$0.50Context: 1M → 262KMistral Small 4thinkingOpenn/a—$0.015Context: 1M → 262KMinistral 3 14B 2512non-thinkingOpenn/a—$0.019Context: 1M → 262KMinistral 3 3B 2512Openn/a—$0.008Context: 1M → 131KMinistral 3 8B 2512Openn/a—$0.011Context: 1M → 262KMistral Large 3non-thinkingOpenn/a—$0.031Context: 1M → 262KDevstral Mediumnon-thinkingOpenn/a—$0.40 / $2Context: 1M → 128K+2Magistral Medium 1thinkingn/a——Context: 1M → 40K+1All Mistral models →Benchmarks
in Chat & KnowledgeWatch out 5
Infinite whitespace stream›
In JSON Object mode, include JSON in the system or user prompt to avoid a possible infinite whitespace stream. Source ↗
Content is a list of chunks›
With reasoning_effort high, message.content is a chunk list rather than a plain string; parse thinking and text chunks. Source ↗
Only function calling · Mistral regional endpoints›
Regional endpoints support function calling only and omit Agents, Batch and Files; check regional model availability before routing requests. Source ↗
10% upcharge · Mistral regional endpoints›
Regional inference charges 1.1× standard list prices for input, output, cached reads and cache writes. Source ↗
Reinforcement learning run still in flight›
The public preview reinforcement learning run is still in flight, and Mistral expects further rapid changes as training scales. Source ↗
FAQ
How much does Mistral Large 4 cost?›
$1.36 per 1M input tokens and $4.18 per 1M output tokens; cached input $0.14 per 1M; cheapest via mistralai at $0.68 / $2.09.
Is Mistral Large 4 free to use?›
There is no free API; the cheapest paid price is $0.68 per 1M input tokens.
How good is Mistral Large 4, and what is it best at?›
#62 of 334 in Chat & Knowledge, #23 of 132 in Coding, #19 of 133 in Agents & Tool Use, #90 of 195 in Writing & Language, #39 of 124 in Vision & Documents. Strongest at: Coding, Agents & work tasks, Reasoning, Long context.
Is Mistral Large 4 better than Gemini 3.1 Pro Preview?›
On FrontierMath Tier 4 (v2), Mistral Large 4 scores 26.8 vs 26.8 — about the same.
How can I use Mistral Large 4?›
Through the API of Mistral.
What is the context window of Mistral Large 4?›
1M tokens, with up to 262K output tokens.
When was Mistral Large 4 released? Is there a newer version?›
Released 2026-10-06. It is the current version in its line.
Is Mistral Large 4 open source?›
No, Mistral Large 4 is a closed model available through an API. The closest open-weights option here is Kimi K3.
Can Mistral Large 4 read images?›
It accepts text and images, PDF files as input.
What is Mistral Large 4?›
Mistral Large 4 is a closed language model from Mistral, released Oct 2026, the successor to Mistral Large 3.
What are the best alternatives to Mistral Large 4?›
GPT-5.6 Luna (cheaper), GPT-6 Luna (better), Kimi K3 (open weights).