Reasoning · Mistral AI

Mistral Large 3 on GPQA Diamond: score, rank and what it means

Mistral Large 3 scores 79.6 on GPQA Diamond, placing it #65 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
79.6
0–100 scale
Rank
#65
of 600
Percentile
89th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
7.4
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with Mistral Large 3 highlighted. Longer bars mean higher scores.

GPT-5.2 Reasoning 87.0
GPT-5.1 Max 86.4
Claude Opus 4.5 Pro 86.0
GPT-5.1 Reasoning 85.6
Claude Sonnet 4.5 Reasoning 85.2
GPT-5.2 84.9
o4 Turbo 84.8
Claude Opus 4.5 Max 84.6
Grok 4 Turbo 84.5
Claude Sonnet 4.5 Max 84.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
2 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
3 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
4 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
5 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
6 GPT-5.2 OpenAI 2000000 $19.71 88.0
7 o4 Turbo OpenAI 2000000 $19.34 86.6
8 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
9 Grok 4 Turbo xAI 1000000 $19.21 86.7
10 Claude Sonnet 4.5 Max Anthropic 1000000 $19.90 87.2

What this score means

On GPQA Diamond, Mistral Large 3 sits at #65 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 7.4 points. The median model in this index scores 68.8, which puts Mistral Large 3 above the midpoint.

Mistral AI models average 63.3 on this benchmark. Mistral Large 3 is 16.3 points above that provider line, so it is a stronger result than the average Mistral AI model.

Among multimodal models, the average is 73.5. Mistral Large 3 is 6.1 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 79.6 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 $5.41 per million input tokens, Mistral Large 3 is above the median input price of $4.00 across the 600 models scored on GPQA Diamond. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Qwen3-Max Reasoning Alibaba Cloud 2000000 $18.12 85.9
Claude 3.7 Sonnet Turbo Anthropic 200000 $15.56 82.3
DeepSeek-V3.2 DeepSeek 1000000 $5.88 84.0
Claude Sonnet 4.5 Vision Anthropic 128000 $16.99 83.8
Mistral Large 3 Mistral AI 128000 $5.41 81.7
o3 Reasoning OpenAI 200000 $18.07 85.3
Llama 4 Maverick Instruct Meta AI 200000 $5.33 81.7

Other benchmarks for Mistral Large 3

BenchmarkScoreRankPercentileRelative
MMLU-Pro 84.6 71 88th
SWE-bench Verified 71.3 89 85th
HumanEval 88.6 62 90th
MATH-500 84.1 123 80th
AIME 2025 78.3 110 82th
LiveCodeBench 74.4 101 83th
IFEval 89.8 75 88th
TruthfulQA 83.7 89 85th
HellaSwag 88.2 135 78th
MMMU 76.2 134 78th
Arena Elo 1448.6 76 87th

FAQ

What score does Mistral Large 3 get on GPQA Diamond?

Mistral Large 3 scores 79.6 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does Mistral Large 3 rank on GPQA Diamond?

It ranks #65 of 600 models, in the 89th percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is Mistral Large 3 good at GPQA Diamond?

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 GPQA Diamond score calculated?

GPQA Diamond is a reasoning 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 Mistral Large 3 cost?

Mistral Large 3 costs $5.41 per million input tokens and $23.83 per million output tokens.

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