Knowledge · Mistral AI

Magistral Chat on MMLU-Pro: score, rank and what it means

Magistral Chat scores 77.9 on MMLU-Pro, placing it #246 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
77.9
0–100 scale
Rank
#246
of 600
Percentile
59th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
13.7
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with Magistral Chat highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 91.6
GPT-5.1 Max 91.3
Claude Opus 4.5 Pro 91.2
Claude Opus 4.5 Reasoning 90.7
Gemini 3 Pro Reasoning 90.1
GPT-5.1 Reasoning 90.0
GPT-5.2 89.9
Claude Opus 4.5 Max 89.5
GPT-5.2 Vision 89.5
Gemini 3 Pro Max 89.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
3 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
4 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
5 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
6 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
7 GPT-5.2 OpenAI 2000000 $19.71 88.0
8 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
9 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4
10 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9

What this score means

On MMLU-Pro, Magistral Chat sits at #246 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 13.7 points. The median model in this index scores 76.1, which puts Magistral Chat above the midpoint.

Mistral AI models average 71.4 on this benchmark. Magistral Chat is 6.5 points above that provider line, so it is a stronger result than the average Mistral AI model.

Among multimodal models, the average is 80.0. Magistral Chat is 2.1 points below that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 77.9 as a relative signal, not an absolute guarantee. Benchmark scores depend on prompt format, evaluation harness and contamination controls. Use this page to narrow the shortlist, then test the model on your own data.

Price context

At $4.33 per million input tokens, Magistral Chat is above the median input price of $4.00 across the 600 models scored on MMLU-Pro. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Llama 3 Lambda Base Lambda 8192 $3.19 72.9
Llama 3.3 Groq Groq 32768 $3.98 76.8
DeepSeek-Coder Chat DeepSeek 200000 $4.20 77.3
Llama 3.3 Chat Meta AI 32768 $4.18 76.9
Magistral Chat Mistral AI 128000 $4.33 76.8
Nova Lite Turbo Amazon 8192 $9.14 73.2
Reka Flash Turbo Reka AI 128000 $10.19 75.1

Other benchmarks for Magistral Chat

BenchmarkScoreRankPercentileRelative
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

FAQ

What score does Magistral Chat get on MMLU-Pro?

Magistral Chat scores 77.9 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does Magistral Chat rank on MMLU-Pro?

It ranks #246 of 600 models, in the 59th percentile. The leader is GPT-5.2 Pro at 91.6.

Is Magistral Chat good at MMLU-Pro?

Yes, relative to the index: it is above the median and inside the top half of scores. The result should be read alongside its price and context window.

How is the MMLU-Pro score calculated?

MMLU-Pro is a knowledge benchmark. Scores in this index are modelled estimates on a 0–100 scale (or Elo for Arena), derived from capability tier and benchmark difficulty. They are not official leaderboard results.

What does Magistral Chat cost?

Magistral Chat costs $4.33 per million input tokens and $16.06 per million output tokens.

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