Knowledge · Hugging Face

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

Zephyr 7B scores 52.8 on MMLU-Pro, placing it #582 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
52.8
0–100 scale
Rank
#582
of 600
Percentile
3th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
38.8
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with Zephyr 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, Zephyr 7B sits at #582 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 38.8 points. The median model in this index scores 76.1, which puts Zephyr 7B below the midpoint.

Hugging Face models average 60.1 on this benchmark. Zephyr 7B is 7.3 points below that provider line, so it is a weaker result than the average Hugging Face model.

Among small open-weight models, the average is 59.8. Zephyr 7B is 7.0 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 52.8 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 $0.23 per million input tokens, Zephyr 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
GPT-NeoX 8B EleutherAI 16384 $0.25 43.7
Llama 3 Hyperbolic 1.5B Hyperbolic 32768 $0.45 48.4
Nemotron Nano 8B NVIDIA 8192 $0.46 48.1
DBRX 1.5B Databricks 16384 $0.32 47.0
Zephyr 7B Hugging Face 32768 $0.23 42.5
Arctic 1.5B Snowflake 32768 $0.15 43.2
Mixtral 1.5B Mistral AI 16384 $0.36 47.7

Other benchmarks for Zephyr 7B

BenchmarkScoreRankPercentileRelative
GPQA Diamond 37.4 593 1th
SWE-bench Verified 25.2 595 1th
HumanEval 42.6 595 1th
MATH-500 43.1 586 2th
AIME 2025 25.6 593 1th
LiveCodeBench 27.6 589 2th
IFEval 56.5 586 2th
TruthfulQA 51.5 587 2th
HellaSwag 64.4 587 2th
MMMU 41.2 592 1th
Arena Elo 1129.9 594 1th

FAQ

What score does Zephyr 7B get on MMLU-Pro?

Zephyr 7B scores 52.8 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does Zephyr 7B rank on MMLU-Pro?

It ranks #582 of 600 models, in the 3rd percentile. The leader is GPT-5.2 Pro at 91.6.

Is Zephyr 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 Zephyr 7B cost?

Zephyr 7B costs $0.23 per million input tokens and $0.93 per million output tokens.

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