Knowledge · EleutherAI

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

Pythia 7B scores 50.4 on MMLU-Pro, placing it #592 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
50.4
0–100 scale
Rank
#592
of 600
Percentile
1th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
41.2
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with Pythia 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, Pythia 7B sits at #592 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 41.2 points. The median model in this index scores 76.1, which puts Pythia 7B below the midpoint.

EleutherAI models average 58.0 on this benchmark. Pythia 7B is 7.6 points below that provider line, so it is a weaker result than the average EleutherAI model.

Among small open-weight models, the average is 59.8. Pythia 7B is 9.4 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 50.4 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 $0.10 per million input tokens, Pythia 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
OLMo 2 1.5B Allen Institute for AI 16384 $0.28 44.0
SmolLM3 8B Hugging Face 32768 $0.21 44.0
Molmo 1.5B Allen Institute for AI 8192 $0.21 42.8
Nemotron Nano 1.5B NVIDIA 8192 $0.10 41.5
Pythia 7B EleutherAI 8192 $0.10 40.7
Pythia 8B EleutherAI 32768 $0.16 41.4
StableLM 2 7B Stability AI 8192 $0.28 44.3

Other benchmarks for Pythia 7B

BenchmarkScoreRankPercentileRelative
GPQA Diamond 35.1 596 1th
SWE-bench Verified 26.8 589 2th
HumanEval 42.9 593 1th
MATH-500 42.3 589 2th
AIME 2025 24.1 596 1th
LiveCodeBench 25.9 591 2th
IFEval 52.4 595 1th
TruthfulQA 47.1 597 1th
HellaSwag 61.7 593 1th
MMMU 38.7 597 1th
Arena Elo 1137.4 588 2th

FAQ

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

Pythia 7B scores 50.4 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does Pythia 7B rank on MMLU-Pro?

It ranks #592 of 600 models, in the 1st percentile. The leader is GPT-5.2 Pro at 91.6.

Is Pythia 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 Pythia 7B cost?

Pythia 7B costs $0.10 per million input tokens and $0.36 per million output tokens.

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