Knowledge · Mistral AI

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

Mixtral Base scores 75.7 on MMLU-Pro, placing it #313 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
75.7
0–100 scale
Rank
#313
of 600
Percentile
48th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
15.9
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with Mixtral Base 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 Base sits at #313 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 15.9 points. The median model in this index scores 76.1, which puts Mixtral Base below the midpoint.

Mistral AI models average 71.4 on this benchmark. Mixtral Base is 4.3 points above that provider line, so it is a stronger result than the average Mistral AI model.

Among open-weight models, the average is 72.1. Mixtral Base is 3.6 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 75.7 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 $2.95 per million input tokens, Mixtral Base 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 Replicate Instruct Replicate 128000 $3.71 75.1
Llama 3.1 Turbo Base Together AI 16384 $3.30 73.0
Seed-OSS Base ByteDance 16384 $3.14 72.2
Fusion Pro OpenRouter 65536 $8.69 72.2
Mixtral Base Mistral AI 65536 $2.95 71.1
Yi-Large Chat 01.AI 65536 $3.49 73.5
Firefunction Pro Fireworks AI 16384 $9.05 72.9

Other benchmarks for Mixtral Base

BenchmarkScoreRankPercentileRelative
GPQA Diamond 64.3 376 37th
SWE-bench Verified 61.4 294 51th
HumanEval 73.7 363 40th
MATH-500 76.8 285 53th
AIME 2025 66.7 319 47th
LiveCodeBench 62.0 349 42th
IFEval 81.2 299 50th
TruthfulQA 72.8 372 38th
HellaSwag 81.0 371 38th
MMMU 66.6 364 39th
Arena Elo 1345.3 372 38th

FAQ

What score does Mixtral Base get on MMLU-Pro?

Mixtral Base scores 75.7 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does Mixtral Base rank on MMLU-Pro?

It ranks #313 of 600 models, in the 48th percentile. The leader is GPT-5.2 Pro at 91.6.

Is Mixtral Base 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 Base cost?

Mixtral Base costs $2.95 per million input tokens and $12.22 per million output tokens.

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