Knowledge · Mistral AI

Mixtral 7B on MMLU-Pro: score, rank and what it means

Mixtral 7B scores 61.8 on MMLU-Pro, placing it #505 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
61.8
0–100 scale
Rank
#505
of 600
Percentile
16th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
29.8
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with Mixtral 7B highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 91.6
GPT-5.1 Max 91.3
Claude Opus 4.5 Pro 91.2
Claude Opus 4.5 Reasoning 90.7
Gemini 3 Pro Reasoning 90.1
GPT-5.1 Reasoning 90.0
GPT-5.2 89.9
Claude Opus 4.5 Max 89.5
GPT-5.2 Vision 89.5
Gemini 3 Pro Max 89.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
3 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
4 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
5 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
6 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
7 GPT-5.2 OpenAI 2000000 $19.71 88.0
8 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
9 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4
10 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9

What this score means

On MMLU-Pro, Mixtral 7B sits at #505 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 29.8 points. The median model in this index scores 76.1, which puts Mixtral 7B below the midpoint.

Mistral AI models average 71.4 on this benchmark. Mixtral 7B is 9.6 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 59.8. Mixtral 7B is 2.0 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 61.8 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 MMLU-Pro. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Llama 3 Hyperbolic 8B Hyperbolic 16384 $0.92 56.0
Mixtral 8B Mistral AI 8192 $0.91 55.4
Yi-Lightning 7B 01.AI 32768 $1.00 55.9
Phi-4 8B Microsoft 32768 $0.96 54.9
Mixtral 7B Mistral AI 16384 $0.70 54.1
DeepSeek-Coder 7B DeepSeek 32768 $1.14 57.3
Command R+ 7B Cohere 8192 $0.95 56.2

Other benchmarks for Mixtral 7B

BenchmarkScoreRankPercentileRelative
GPQA Diamond 50.8 513 15th
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 MMLU-Pro?

Mixtral 7B scores 61.8 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does Mixtral 7B rank on MMLU-Pro?

It ranks #505 of 600 models, in the 16th percentile. The leader is GPT-5.2 Pro at 91.6.

Is Mixtral 7B good at MMLU-Pro?

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 MMLU-Pro score calculated?

MMLU-Pro is a knowledge 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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