Knowledge · Hugging Face

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

Zephyr Base scores 65.4 on MMLU-Pro, placing it #447 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
65.4
0–100 scale
Rank
#447
of 600
Percentile
26th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
26.2
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with Zephyr 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, Zephyr Base sits at #447 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 26.2 points. The median model in this index scores 76.1, which puts Zephyr Base below the midpoint.

Hugging Face models average 60.1 on this benchmark. Zephyr Base is 5.3 points above that provider line, so it is a stronger result than the average Hugging Face model.

Among open-weight models, the average is 72.1. Zephyr Base is 6.7 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 65.4 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 $1.26 per million input tokens, Zephyr 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
GLM-4.6 7B Zhipu AI 16384 $1.52 61.8
Mistral Large 3 7B Mistral AI 32768 $1.44 61.1
Llama 3.1 8B Meta AI 8192 $1.15 58.7
MiniMax-M2 8B MiniMax 32768 $1.65 61.7
Zephyr Base Hugging Face 4096 $1.26 59.5
Pythia Instruct EleutherAI 8192 $1.41 60.8
Yi-Lightning 8B 01.AI 4096 $1.16 59.2

Other benchmarks for Zephyr Base

BenchmarkScoreRankPercentileRelative
GPQA Diamond 57.2 438 27th
SWE-bench Verified 42.4 498 17th
HumanEval 64.8 443 26th
MATH-500 62.6 440 27th
AIME 2025 51.0 452 25th
LiveCodeBench 47.9 468 22th
IFEval 70.3 456 24th
TruthfulQA 65.1 458 24th
HellaSwag 73.1 480 20th
MMMU 54.2 506 16th
Arena Elo 1270.3 458 24th

FAQ

What score does Zephyr Base get on MMLU-Pro?

Zephyr Base scores 65.4 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does Zephyr Base rank on MMLU-Pro?

It ranks #447 of 600 models, in the 26th percentile. The leader is GPT-5.2 Pro at 91.6.

Is Zephyr 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 Zephyr Base cost?

Zephyr Base costs $1.26 per million input tokens and $6.45 per million output tokens.

Related