Reasoning · Mistral AI

Mixtral 7B on GPQA Diamond: score, rank and what it means

Mixtral 7B scores 50.8 on GPQA Diamond, placing it #513 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
50.8
0–100 scale
Rank
#513
of 600
Percentile
15th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
36.2
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with Mixtral 7B 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 7B sits at #513 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 36.2 points. The median model in this index scores 68.8, which puts Mixtral 7B below the midpoint.

Mistral AI models average 63.3 on this benchmark. Mixtral 7B is 12.5 points below that provider line, so it is a weaker result than the average Mistral AI model.

Among small open-weight models, the average is 49.3. Mixtral 7B is 1.5 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 50.8 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 $0.70 per million input tokens, Mixtral 7B 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
QwQ 7B Alibaba Cloud 8192 $1.11 58.1
Pythia Base EleutherAI 16384 $0.99 55.9
Llama 3 Replicate 7B Replicate 32768 $0.91 56.0
Mixtral Groq 8B Groq 32768 $0.77 54.8
Mixtral 7B Mistral AI 16384 $0.70 54.1
Nemotron 4 8B NVIDIA 4096 $1.06 57.9
Fusion Nano OpenRouter 8192 $2.96 56.8

Other benchmarks for Mixtral 7B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 61.8 505 16th
SWE-bench Verified 38.7 532 11th
HumanEval 56.8 532 11th
MATH-500 51.6 545 9th
AIME 2025 42.3 530 12th
LiveCodeBench 41.7 528 12th
IFEval 66.5 512 15th
TruthfulQA 59.9 531 12th
HellaSwag 70.3 531 12th
MMMU 54.6 502 16th
Arena Elo 1216.6 537 11th

FAQ

What score does Mixtral 7B get on GPQA Diamond?

Mixtral 7B scores 50.8 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does Mixtral 7B rank on GPQA Diamond?

It ranks #513 of 600 models, in the 15th percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is Mixtral 7B good at GPQA Diamond?

It is below the median for this benchmark, so test it carefully before relying on it for this capability. 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 7B cost?

Mixtral 7B costs $0.70 per million input tokens and $3.13 per million output tokens.

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