Reasoning · Mistral AI

Mixtral on GPQA Diamond: score, rank and what it means

Mixtral scores 71.3 on GPQA Diamond, placing it #234 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
71.3
0–100 scale
Rank
#234
of 600
Percentile
61th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
15.7
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with Mixtral 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, Mixtral sits at #234 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 15.7 points. The median model in this index scores 68.8, which puts Mixtral above the midpoint.

Mistral AI models average 63.3 on this benchmark. Mixtral is 8.0 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. Mixtral is 2.2 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 71.3 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 $3.48 per million input tokens, Mixtral is below 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
Gemma 3 Google DeepMind 65536 $3.68 73.6
GPT-5.1 Mini OpenAI 128000 $12.19 77.7
Llama 3 Lambda Chat Lambda 32768 $3.73 74.7
Llama 3.3 Base Meta AI 32768 $3.63 74.0
Mixtral Mistral AI 65536 $3.48 73.7
GPT-5.1 Nano OpenAI 32768 $9.56 74.1
Reka Flash Pro Reka AI 200000 $10.82 75.2

Other benchmarks for Mixtral

BenchmarkScoreRankPercentileRelative
MMLU-Pro 77.3 269 55th
SWE-bench Verified 60.3 321 47th
HumanEval 75.9 330 45th
MATH-500 78.5 249 59th
AIME 2025 72.2 215 64th
LiveCodeBench 62.5 342 43th
IFEval 81.2 298 50th
TruthfulQA 76.4 297 51th
HellaSwag 82.8 326 46th
MMMU 72.7 228 62th
Arena Elo 1363.2 337 44th

FAQ

What score does Mixtral get on GPQA Diamond?

Mixtral scores 71.3 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does Mixtral rank on GPQA Diamond?

It ranks #234 of 600 models, in the 61st percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is Mixtral 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 Mixtral cost?

Mixtral costs $3.48 per million input tokens and $12.73 per million output tokens.

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