Knowledge · Groq

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

Mixtral Groq scores 75.1 on MMLU-Pro, placing it #331 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
75.1
0–100 scale
Rank
#331
of 600
Percentile
45th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
16.5
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with Mixtral Groq 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 Groq sits at #331 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 16.5 points. The median model in this index scores 76.1, which puts Mixtral Groq below the midpoint.

Groq models average 68.9 on this benchmark. Mixtral Groq is 6.2 points above that provider line, so it is a stronger result than the average Groq model.

Among open-weight models, the average is 72.1. Mixtral Groq is 3.0 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 75.1 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 $3.37 per million input tokens, Mixtral Groq 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
Gemma 3 Base Google DeepMind 65536 $3.09 71.1
Llama 3.1 Base Meta AI 32768 $3.39 72.2
Fusion Max OpenRouter 65536 $9.14 72.5
Gemma 3 Google DeepMind 65536 $3.68 73.6
Mixtral Groq Groq 16384 $3.37 73.1
Claude 3.7 Sonnet Mini Anthropic 32768 $9.74 73.0
Llama 3 Baseten Chat Baseten 200000 $3.55 73.2

Other benchmarks for Mixtral Groq

BenchmarkScoreRankPercentileRelative
GPQA Diamond 66.1 343 43th
SWE-bench Verified 62.0 281 53th
HumanEval 78.7 271 55th
MATH-500 74.9 329 45th
AIME 2025 67.5 303 50th
LiveCodeBench 64.1 314 48th
IFEval 81.2 300 50th
TruthfulQA 78.6 235 61th
HellaSwag 85.0 247 59th
MMMU 70.7 280 53th
Arena Elo 1388.6 254 58th

FAQ

What score does Mixtral Groq get on MMLU-Pro?

Mixtral Groq scores 75.1 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does Mixtral Groq rank on MMLU-Pro?

It ranks #331 of 600 models, in the 45th percentile. The leader is GPT-5.2 Pro at 91.6.

Is Mixtral Groq 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 Groq cost?

Mixtral Groq costs $3.37 per million input tokens and $15.23 per million output tokens.

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