Mistral AI · multimodal · Released 2025-06-25

Magistral Chat: pricing, context window and benchmarks

Magistral Chat is a multimodal model from Mistral AI. It offers a 128,000-token context window, costs $4.33 per million input tokens and $16.06 per million output tokens, and averages 76.8 across the index's benchmark suite.

codingvisionopen weightsmultimodal
Input price
$4.33
per 1M tokens
Output price
$16.06
per 1M tokens
Context
128,000
tokens
Avg score
76.8
rank #199 of 600
Arena Elo
1397.1
modelled
Max output
16,384
tokens

Pricing

Magistral Chat costs $4.33 per million input tokens and $16.06 per million output tokens. A blended 3:1 input-to-output mix works out to about $7.26 per million tokens. Cached input is listed at $0.39 per million tokens.

ItemPriceNotes
Input$4.33per 1M tokens
Output$16.06per 1M tokens
Cached input$0.39per 1M tokens
Blended 3:1$7.26estimate per 1M tokens
1M in + 1M out$20.39estimate

Benchmarks

Scores below are modelled estimates on a 0–100 scale. Use them to compare relative position, not as official vendor results.

BenchmarkScoreRankPercentileRelative
MMLU-Pro 77.9 246 59th
GPQA Diamond 72.3 214 64th
SWE-bench Verified 64.5 222 63th
HumanEval 81.3 207 66th
MATH-500 83.8 128 79th
AIME 2025 73.7 192 68th
LiveCodeBench 67.5 238 60th
IFEval 83.5 231 62th
TruthfulQA 82.3 124 79th
HellaSwag 86.1 213 65th
MMMU 72.0 246 59th
Arena Elo 1397.1 217 64th

What Magistral Chat is good for

Magistral Chat is tuned toward coding work. It is a reasonable candidate for code generation, review, debugging and repository-scale tasks, especially when paired with a retrieval layer. At $4.33 per million input tokens, it sits in the mid-range of the index, and the 128,000-token context window is enough for large files and multi-file diffs.

Strengths

  • Large 128,000-token context window for long documents and agent traces.
  • Open weights make self-hosting, fine-tuning and data-residency review possible.
  • Accepts more than text, including image input where the provider supports it.
  • Coding benchmarks are a relative strength within its tier.

Trade-offs

  • No standout weakness in the indexed specifications, but real-world behaviour still needs testing.

How it compares

ModelProviderContextInput / 1MAvg score
Llama 3.1 Turbo Together AI 200000 $4.17 76.8
Llama 3.3 Groq Groq 32768 $3.98 76.8
Llama 3.3 Groq Chat Groq 32768 $4.06 76.8
Magistral Chat Mistral AI 128000 $4.33 76.8
ERNIE 4.0 Baidu 32768 $11.37 76.7
Llama 3.1 Turbo Instruct Together AI 32768 $4.21 76.7

Browse all comparisons →

FAQ

How much does Magistral Chat cost?

Magistral Chat is listed at $4.33 per million input tokens and $16.06 per million output tokens. Cached input is $0.39 per million tokens. A blended 3:1 input-to-output mix is about $7.26 per million tokens.

What is the context window of Magistral Chat?

Magistral Chat has a context window of 128,000 tokens and can emit up to 16,384 output tokens per request in this index.

Is Magistral Chat open weights?

Yes. Magistral Chat is listed as an open-weight model under a open weights licence.

How does Magistral Chat score on benchmarks?

Magistral Chat averages 76.8 across the scored benchmarks in this index, ranking #199 of 600 models. Its strongest relative result is Arena Elo at 1397.1.

What is Magistral Chat best for?

Magistral Chat is tuned toward coding work. It is a reasonable candidate for code generation, review, debugging and repository-scale tasks, especially when paired with a retrieval layer. At $4.33 per million input tokens, it sits in the mid-range of the index, and the 128,000-token context window is enough for large files and multi-file diffs.

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