Mathematics · EleutherAI

Pythia 7B on MATH-500: score, rank and what it means

Pythia 7B scores 42.3 on MATH-500, placing it #589 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
42.3
0–100 scale
Rank
#589
of 600
Percentile
2th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
54.4
points

Score distribution

The chart shows the top 10 models on MATH-500, with Pythia 7B highlighted. Longer bars mean higher scores.

GPT-5.2 Max 96.7
GPT-5.1 Reasoning 95.9
GPT-5.1 Pro 95.1
o4 Reasoning 94.8
Grok 4 Max 94.6
Grok 4 Reasoning 94.4
Claude Opus 4.5 Max 94.2
Claude Opus 4.5 93.7
Gemini 3 Pro Reasoning 93.3
Claude Opus 4.5 Turbo 93.2

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
3 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
4 o4 Reasoning OpenAI 1000000 $19.69 87.5
5 Grok 4 Max xAI 2000000 $19.70 86.6
6 Grok 4 Reasoning xAI 2000000 $19.67 87.8
7 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
8 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
9 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
10 Claude Opus 4.5 Turbo Anthropic 2000000 $19.57 85.7

What this score means

On MATH-500, Pythia 7B sits at #589 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 54.4 points. The median model in this index scores 76.0, which puts Pythia 7B below the midpoint.

EleutherAI models average 52.0 on this benchmark. Pythia 7B is 9.7 points below that provider line, so it is a weaker result than the average EleutherAI model.

Among small open-weight models, the average is 53.7. Pythia 7B is 11.4 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 42.3 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 $0.10 per million input tokens, Pythia 7B is below the median input price of $4.00 across the 600 models scored on MATH-500. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Phi-3.5 1.5B Microsoft 32768 $0.25 44.5
Zephyr 7B Hugging Face 32768 $0.23 42.5
GPT-NeoX 7B EleutherAI 8192 $0.20 42.4
StableLM 2 7B Stability AI 8192 $0.28 44.3
Pythia 7B EleutherAI 8192 $0.10 40.7
GPT-NeoX 8B EleutherAI 16384 $0.25 43.7
OLMo 2 1.5B Allen Institute for AI 16384 $0.28 44.0

Other benchmarks for Pythia 7B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 50.4 592 1th
GPQA Diamond 35.1 596 1th
SWE-bench Verified 26.8 589 2th
HumanEval 42.9 593 1th
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 MATH-500?

Pythia 7B scores 42.3 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Pythia 7B rank on MATH-500?

It ranks #589 of 600 models, in the 2nd percentile. The leader is GPT-5.2 Max at 96.7.

Is Pythia 7B good at MATH-500?

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 MATH-500 score calculated?

MATH-500 is a mathematics 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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