Knowledge · Groq

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

Mixtral Groq 7B scores 59.3 on MMLU-Pro, placing it #532 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
59.3
0–100 scale
Rank
#532
of 600
Percentile
11th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
32.3
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with Mixtral Groq 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 Groq 7B sits at #532 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 32.3 points. The median model in this index scores 76.1, which puts Mixtral Groq 7B below the midpoint.

Groq models average 68.9 on this benchmark. Mixtral Groq 7B is 9.6 points below that provider line, so it is a weaker result than the average Groq model.

Among small open-weight models, the average is 59.8. Mixtral Groq 7B is 0.5 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 59.3 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 $0.70 per million input tokens, Mixtral Groq 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 Novita 7B Novita AI 8192 $0.92 56.3
Yi-Large 8B 01.AI 32768 $0.88 56.1
Llama 4 Maverick 1.5B Meta AI 8192 $0.93 55.2
MiniMax-M2 1.5B MiniMax 16384 $0.84 54.6
Mixtral Groq 7B Groq 4096 $0.70 53.4
OLMo 2 7B Allen Institute for AI 16384 $0.56 51.7
Phi-3.5 7B Microsoft 4096 $0.50 50.5

Other benchmarks for Mixtral Groq 7B

BenchmarkScoreRankPercentileRelative
GPQA Diamond 47.5 544 9th
SWE-bench Verified 36.6 545 9th
HumanEval 58.5 519 14th
MATH-500 51.1 546 9th
AIME 2025 43.2 520 13th
LiveCodeBench 43.2 515 14th
IFEval 65.7 525 13th
TruthfulQA 60.1 529 12th
HellaSwag 71.8 504 16th
MMMU 50.2 551 8th
Arena Elo 1227.8 529 12th

FAQ

What score does Mixtral Groq 7B get on MMLU-Pro?

Mixtral Groq 7B scores 59.3 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does Mixtral Groq 7B rank on MMLU-Pro?

It ranks #532 of 600 models, in the 11th percentile. The leader is GPT-5.2 Pro at 91.6.

Is Mixtral Groq 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 Groq 7B cost?

Mixtral Groq 7B costs $0.70 per million input tokens and $2.47 per million output tokens.

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