Pythia 8B on MATH-500: score, rank and what it means
Pythia 8B scores 37.9 on MATH-500, placing it #595 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.
Score distribution
The chart shows the top 10 models on MATH-500, with Pythia 8B highlighted. Longer bars mean higher scores.
Top 10 leaderboard
| # | Model | Provider | Context | Input / 1M | Avg 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 8B sits at #595 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 58.8 points. The median model in this index scores 76.0, which puts Pythia 8B below the midpoint.
EleutherAI models average 52.0 on this benchmark. Pythia 8B is 14.1 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 8B is 15.8 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 37.9 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 $0.16 per million input tokens, Pythia 8B 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.
| Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|
| OLMo 2 1.5B | Allen Institute for AI | 16384 | $0.28 | 44.0 |
| Nemotron Nano 1.5B | NVIDIA | 8192 | $0.10 | 41.5 |
| Zephyr 8B | Hugging Face | 8192 | $0.22 | 43.0 |
| Molmo 1.5B | Allen Institute for AI | 8192 | $0.21 | 42.8 |
| Pythia 8B | EleutherAI | 32768 | $0.16 | 41.4 |
| SmolLM3 1.5B | Hugging Face | 8192 | $0.04 | 36.8 |
| GPT-NeoX 1.5B | EleutherAI | 32768 | $0.06 | 36.4 |
Other benchmarks for Pythia 8B
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 50.3 | 593 | 1th | |
| GPQA Diamond | 38.2 | 592 | 1th | |
| SWE-bench Verified | 27.3 | 588 | 2th | |
| HumanEval | 42.8 | 594 | 1th | |
| AIME 2025 | 29.8 | 584 | 3th | |
| LiveCodeBench | 24.1 | 594 | 1th | |
| IFEval | 53.9 | 593 | 1th | |
| TruthfulQA | 49.7 | 594 | 1th | |
| HellaSwag | 60.7 | 595 | 1th | |
| MMMU | 40.5 | 593 | 1th | |
| Arena Elo | 1130.8 | 592 | 1th |
FAQ
What score does Pythia 8B get on MATH-500?
Pythia 8B scores 37.9 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.
How does Pythia 8B rank on MATH-500?
It ranks #595 of 600 models, in the 1st percentile. The leader is GPT-5.2 Max at 96.7.
Is Pythia 8B 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 8B cost?
Pythia 8B costs $0.16 per million input tokens and $0.79 per million output tokens.