Multimodal · Mistral AI

Magistral Base on MMMU: score, rank and what it means

Magistral Base scores 72.2 on MMMU, placing it #236 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
72.2
0–100 scale
Rank
#236
of 600
Percentile
61th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
14.7
points

Score distribution

The chart shows the top 10 models on MMMU, with Magistral Base highlighted. Longer bars mean higher scores.

GPT-5.2 Max 86.9
GPT-5.1 Reasoning 86.2
GPT-5.2 85.3
Claude Sonnet 4.5 Reasoning 85.2
GPT-5.1 Max 85.1
Grok 4 Pro 84.9
Claude Opus 4.5 Reasoning 84.6
Claude Sonnet 4.5 Pro 84.5
GPT-5.2 Pro 84.4
GPT-5.2 Vision 84.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
3 GPT-5.2 OpenAI 2000000 $19.71 88.0
4 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
5 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
6 Grok 4 Pro xAI 1000000 $19.00 85.4
7 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
8 Claude Sonnet 4.5 Pro Anthropic 1000000 $18.73 86.7
9 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
10 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4

What this score means

On MMMU, Magistral Base sits at #236 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 14.7 points. The median model in this index scores 70.0, which puts Magistral Base above the midpoint.

Mistral AI models average 64.8 on this benchmark. Magistral Base is 7.4 points above that provider line, so it is a stronger result than the average Mistral AI model.

Among multimodal models, the average is 74.3. Magistral Base 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 72.2 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 MMMU. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Gemma 3 Instruct Google DeepMind 128000 $3.72 74.1
Llama 3 Replicate Chat Replicate 200000 $3.74 74.7
Llama 3 Lambda Chat Lambda 32768 $3.73 74.7
Nova Lite Amazon 65536 $9.20 73.4
Magistral Base Mistral AI 65536 $3.86 75.6
Reka Flash Reasoning Reka AI 32768 $10.70 75.6
Reka Flash Turbo Reka AI 128000 $10.19 75.1

Other benchmarks for Magistral Base

BenchmarkScoreRankPercentileRelative
MMLU-Pro 80.7 159 74th
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
Arena Elo 1378.9 276 54th

FAQ

What score does Magistral Base get on MMMU?

Magistral Base scores 72.2 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does Magistral Base rank on MMMU?

It ranks #236 of 600 models, in the 61st percentile. The leader is GPT-5.2 Max at 86.9.

Is Magistral Base good at MMMU?

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 MMMU score calculated?

MMMU is a multimodal 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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