Knowledge · Mistral AI

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

Magistral Base scores 80.7 on MMLU-Pro, placing it #159 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
80.7
0–100 scale
Rank
#159
of 600
Percentile
74th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
10.9
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with Magistral Base 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 Base sits at #159 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 10.9 points. The median model in this index scores 76.1, which puts Magistral Base above the midpoint.

Mistral AI models average 71.4 on this benchmark. Magistral Base is 9.3 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 Base is 0.7 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 80.7 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 $3.86 per million input tokens, Magistral Base is below 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 3.1 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
Magistral Base Mistral AI 65536 $3.86 75.6
o4 Mini OpenAI 200000 $11.92 77.7
Claude Haiku 4.5 Turbo Anthropic 200000 $14.37 80.0

Other benchmarks for Magistral Base

BenchmarkScoreRankPercentileRelative
GPQA Diamond 73.5 185 69th
SWE-bench Verified 65.6 201 67th
HumanEval 78.5 281 53th
MATH-500 76.3 293 51th
AIME 2025 69.1 279 54th
LiveCodeBench 69.7 198 67th
IFEval 83.5 230 62th
TruthfulQA 77.6 266 56th
HellaSwag 85.0 245 59th
MMMU 72.2 236 61th
Arena Elo 1378.9 276 54th

FAQ

What score does Magistral Base get on MMLU-Pro?

Magistral Base scores 80.7 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does Magistral Base rank on MMLU-Pro?

It ranks #159 of 600 models, in the 74th percentile. The leader is GPT-5.2 Pro at 91.6.

Is Magistral Base 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 Base cost?

Magistral Base costs $3.86 per million input tokens and $17.23 per million output tokens.

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