Mathematics · EleutherAI

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

Pythia Instruct scores 63.5 on MATH-500, placing it #429 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
63.5
0–100 scale
Rank
#429
of 600
Percentile
29th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
33.2
points

Score distribution

The chart shows the top 10 models on MATH-500, with Pythia Instruct 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 Instruct sits at #429 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 33.2 points. The median model in this index scores 76.0, which puts Pythia Instruct below the midpoint.

EleutherAI models average 52.0 on this benchmark. Pythia Instruct is 11.5 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 Instruct is 7.3 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 63.5 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 $1.41 per million input tokens, Pythia Instruct 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
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
ERNIE 4.0 Nano Baidu 32768 $4.68 62.1

Other benchmarks for Pythia Instruct

BenchmarkScoreRankPercentileRelative
MMLU-Pro 65.3 448 25th
GPQA Diamond 58.3 424 29th
SWE-bench Verified 47.1 445 26th
HumanEval 66.3 427 29th
AIME 2025 52.3 443 26th
LiveCodeBench 46.8 480 20th
IFEval 72.4 428 29th
TruthfulQA 66.7 435 28th
HellaSwag 73.8 459 24th
MMMU 56.2 485 19th
Arena Elo 1291.1 430 28th

FAQ

What score does Pythia Instruct get on MATH-500?

Pythia Instruct scores 63.5 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Pythia Instruct rank on MATH-500?

It ranks #429 of 600 models, in the 29th percentile. The leader is GPT-5.2 Max at 96.7.

Is Pythia Instruct 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 Instruct cost?

Pythia Instruct costs $1.41 per million input tokens and $5.70 per million output tokens.

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