Mathematics · Mistral AI

Magistral Base on MATH-500: score, rank and what it means

Magistral Base scores 76.3 on MATH-500, placing it #293 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
76.3
0–100 scale
Rank
#293
of 600
Percentile
51th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
20.4
points

Score distribution

The chart shows the top 10 models on MATH-500, with Magistral Base highlighted. Longer bars mean higher scores.

GPT-5.2 Max 96.7
GPT-5.1 Reasoning 95.9
GPT-5.1 Pro 95.1
o4 Reasoning 94.8
Grok 4 Max 94.6
Grok 4 Reasoning 94.4
Claude Opus 4.5 Max 94.2
Claude Opus 4.5 93.7
Gemini 3 Pro Reasoning 93.3
Claude Opus 4.5 Turbo 93.2

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-5.1 Pro OpenAI 200000 $19.77 87.8
4 o4 Reasoning OpenAI 1000000 $19.69 87.5
5 Grok 4 Max xAI 2000000 $19.70 86.6
6 Grok 4 Reasoning xAI 2000000 $19.67 87.8
7 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
8 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
9 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
10 Claude Opus 4.5 Turbo Anthropic 2000000 $19.57 85.7

What this score means

On MATH-500, Magistral Base sits at #293 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 20.4 points. The median model in this index scores 76.0, which puts Magistral Base above the midpoint.

Mistral AI models average 69.1 on this benchmark. Magistral Base is 7.2 points above that provider line, so it is a stronger result than the average Mistral AI model.

Among multimodal models, the average is 81.3. Magistral Base is 5.0 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 76.3 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 MATH-500. 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
Firefunction Reasoning Fireworks AI 8192 $9.08 72.5
DBRX Databricks 65536 $3.29 73.3
Llama 3 Hyperbolic Hyperbolic 65536 $3.86 74.5
Magistral Base Mistral AI 65536 $3.86 75.6
Sonar Perplexity 200000 $10.57 76.0
Yi-Large 01.AI 32768 $3.40 73.5

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
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 MATH-500?

Magistral Base scores 76.3 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Magistral Base rank on MATH-500?

It ranks #293 of 600 models, in the 51st percentile. The leader is GPT-5.2 Max at 96.7.

Is Magistral Base good at MATH-500?

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 MATH-500 score calculated?

MATH-500 is a mathematics 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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