Mistral Large 4
Mistral Large 4Alternatives?
CheaperGPT-6.1 Solmax×12.2-55%$0.72Remove unsupported parameters+5
BetterClaude Haiku 5.5medium+50%-97%$0.047Remove sampling parameters+5
OpenDeepSeek V4.1 Flash 1017max×2.7-84%$0.26No PDF input+5CheaperGPT-6.1 Terramax×12.1-75%$0.40CheaperClaude Opus 5.5medium×9.1-17%$1.34No forced tool use+5GPT-6.1 Solmax×12.2-55%$0.72Remove unsupported parameters+5GPT-6.1 Terramax×12.1-75%$0.40Claude Opus 5.5medium×9.1-17%$1.34No forced tool use+5Claude Sonnet 5.5high×7.2-45%$0.88No forced tool use+5GPT-6 Solmax×6.3-35%$1.04Claude Haiku 5.5medium+50%-97%$0.047Remove sampling parameters+5GPT-6.1 Terralow+60%-97%$0.055GPT-6 Lunamax+80%-96%$0.068Function calling only with none · Chat Completions+3GPT-6.1 Sollow×2.3-92%$0.13Remove unsupported parameters+5GPT-6 Solmedium+80%-85%$0.25DeepSeek V4.1 Flash 1017maxOpen×2.7-84%$0.26No PDF input+5
GLM 5.3maxOpen×2+25%$2.01No image input+5
Kimi K3maxOpen+70%+25%$2.00Sampling parameters are fixed+3DeepSeek V4 Pro 0813maxOpensame-58%$0.67No image input+6
MiMo v2.6 ProthinkingOpensame-92%$0.13No PDF input+4Mistral Medium 3.5highOpenn/a—$0.43Context: 1M → 262KMistral Small 4thinkingOpenn/a—$0.017Context: 1M → 262KMistral Smalln/a—$1 / $3Context: 1M → 32K+1Ministral 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 → 262KMinistral 14B 3.0n/a—$0.20 / $0.20Context: 1M → 128K+1All Mistral models →Benchmarks
in Agents & Tool UseWatch 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. A typical benchmark task costs about $1.61 at default effort.
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?›
#64 of 336 in Chat & Knowledge, #25 of 134 in Coding, #21 of 135 in Agents & Tool Use, #89 of 197 in Writing & Language, #40 of 125 in Vision & Documents. Strongest at: Coding, Agents & work tasks, Reasoning, Long context.
Is Mistral Large 4 better than MiMo v2.6 Pro?›
On Terminal-Bench Science 0.1, Mistral Large 4 scores 4.8 vs 5.7 — about the same. It is 1,105% more expensive per task.
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 DeepSeek V4.1 Flash 1017.
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-6.1 Sol (cheaper), Claude Haiku 5.5 (better), DeepSeek V4.1 Flash 1017 (open weights).