Knowledge · Mistral AI

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

Magistral Instruct scores 80.8 on MMLU-Pro, placing it #156 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
80.8
0–100 scale
Rank
#156
of 600
Percentile
74th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
10.8
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with Magistral Instruct 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 Instruct sits at #156 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 10.8 points. The median model in this index scores 76.1, which puts Magistral Instruct above the midpoint.

Mistral AI models average 71.4 on this benchmark. Magistral Instruct is 9.4 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 Instruct is 0.8 points above that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 80.8 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 $4.48 per million input tokens, Magistral Instruct 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
ERNIE 4.0 Max Baidu 32768 $12.40 78.9
ERNIE 4.5 Max Baidu 128000 $14.41 80.6
Llama 3 Lambda Instruct Lambda 32768 $3.92 75.8
Llama 3.1 Turbo Chat Together AI 200000 $3.95 76.1
Magistral Instruct Mistral AI 65536 $4.48 78.4
Hunyuan-Large Tencent 65536 $4.33 78.2
Llama 4 Scout Base Meta AI 32768 $3.95 75.3

Other benchmarks for Magistral Instruct

BenchmarkScoreRankPercentileRelative
GPQA Diamond 73.8 176 71th
SWE-bench Verified 69.8 115 81th
HumanEval 80.5 222 63th
MATH-500 81.7 172 71th
AIME 2025 71.7 224 63th
LiveCodeBench 73.6 118 80th
IFEval 86.7 141 77th
TruthfulQA 78.3 246 59th
HellaSwag 89.0 111 82th
MMMU 76.4 129 79th
Arena Elo 1402.2 203 66th

FAQ

What score does Magistral Instruct get on MMLU-Pro?

Magistral Instruct scores 80.8 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does Magistral Instruct rank on MMLU-Pro?

It ranks #156 of 600 models, in the 74th percentile. The leader is GPT-5.2 Pro at 91.6.

Is Magistral Instruct 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 Instruct cost?

Magistral Instruct costs $4.48 per million input tokens and $22.65 per million output tokens.

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