Mathematics · EleutherAI

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

Pythia scores 63.6 on MATH-500, placing it #428 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
63.6
0–100 scale
Rank
#428
of 600
Percentile
29th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
33.1
points

Score distribution

The chart shows the top 10 models on MATH-500, with Pythia 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 sits at #428 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 33.1 points. The median model in this index scores 76.0, which puts Pythia below the midpoint.

EleutherAI models average 52.0 on this benchmark. Pythia is 11.6 points above that provider line, so it is a stronger result than the average EleutherAI model.

Among open-weight models, the average is 70.8. Pythia is 7.2 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 63.6 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 $1.29 per million input tokens, Pythia 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
DeepSeek-R1 7B DeepSeek 32768 $1.79 63.0
GPT-NeoX EleutherAI 16384 $1.57 61.7
StableLM 2 Base Stability AI 8192 $1.49 61.9
Embed 4 Pro Cohere 4096 $5.05 63.5
Pythia EleutherAI 32768 $1.29 59.8
Pythia Instruct EleutherAI 8192 $1.41 60.8
Qwen3-Coder 8B Alibaba Cloud 32768 $1.43 61.3

Other benchmarks for Pythia

BenchmarkScoreRankPercentileRelative
MMLU-Pro 63.1 487 19th
GPQA Diamond 55.6 455 24th
SWE-bench Verified 44.8 467 22th
HumanEval 62.8 460 23th
AIME 2025 50.0 460 23th
LiveCodeBench 52.2 427 29th
IFEval 70.4 454 24th
TruthfulQA 67.2 426 29th
HellaSwag 72.8 485 19th
MMMU 55.0 497 17th
Arena Elo 1259.9 476 21th

FAQ

What score does Pythia get on MATH-500?

Pythia scores 63.6 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Pythia rank on MATH-500?

It ranks #428 of 600 models, in the 29th percentile. The leader is GPT-5.2 Max at 96.7.

Is Pythia 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 cost?

Pythia costs $1.29 per million input tokens and $5.47 per million output tokens.

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