Pythia Base on MMMU: score, rank and what it means
Pythia Base scores 52.9 on MMMU, placing it #521 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.
Score distribution
The chart shows the top 10 models on MMMU, with Pythia Base 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-5.2 | OpenAI | 2000000 | $19.71 | 88.0 |
| 4 | Claude Sonnet 4.5 Reasoning | Anthropic | 400000 | $19.48 | 87.7 |
| 5 | GPT-5.1 Max | OpenAI | 2000000 | $20.50 | 87.9 |
| 6 | Grok 4 Pro | xAI | 1000000 | $19.00 | 85.4 |
| 7 | Claude Opus 4.5 Reasoning | Anthropic | 2000000 | $20.91 | 88.2 |
| 8 | Claude Sonnet 4.5 Pro | Anthropic | 1000000 | $18.73 | 86.7 |
| 9 | GPT-5.2 Pro | OpenAI | 2000000 | $21.32 | 89.6 |
| 10 | GPT-5.2 Vision | OpenAI | 1000000 | $19.03 | 87.4 |
What this score means
On MMMU, Pythia Base sits at #521 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 34.0 points. The median model in this index scores 70.0, which puts Pythia Base below the midpoint.
EleutherAI models average 50.0 on this benchmark. Pythia Base is 2.9 points above that provider line, so it is a stronger result than the average EleutherAI model.
Among open-weight models, the average is 65.1. Pythia Base is 12.2 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 52.9 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 $0.99 per million input tokens, Pythia Base is below the median input price of $4.00 across the 600 models scored on MMMU. 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 |
|---|---|---|---|---|
| DeepSeek-Coder 7B | DeepSeek | 32768 | $1.14 | 57.3 |
| Gemma 3 8B | Google DeepMind | 16384 | $0.96 | 56.5 |
| Llama 3 DeepInfra 7B | DeepInfra | 16384 | $0.95 | 55.6 |
| Qwen3-Coder 1.5B | Alibaba Cloud | 32768 | $0.76 | 52.8 |
| Pythia Base | EleutherAI | 16384 | $0.99 | 55.9 |
| GLM-4.5 1.5B | Zhipu AI | 16384 | $0.65 | 53.3 |
| Magistral 1.5B | Mistral AI | 4096 | $0.67 | 52.7 |
Other benchmarks for Pythia Base
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 60.5 | 524 | 13th | |
| GPQA Diamond | 51.0 | 510 | 15th | |
| SWE-bench Verified | 43.3 | 488 | 19th | |
| HumanEval | 59.6 | 509 | 15th | |
| MATH-500 | 55.7 | 512 | 15th | |
| AIME 2025 | 43.9 | 510 | 15th | |
| LiveCodeBench | 45.7 | 492 | 18th | |
| IFEval | 68.7 | 482 | 20th | |
| TruthfulQA | 62.1 | 503 | 16th | |
| HellaSwag | 71.9 | 503 | 16th | |
| Arena Elo | 1240.6 | 512 | 15th |
FAQ
What score does Pythia Base get on MMMU?
Pythia Base scores 52.9 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.
How does Pythia Base rank on MMMU?
It ranks #521 of 600 models, in the 13th percentile. The leader is GPT-5.2 Max at 86.9.
Is Pythia Base good at MMMU?
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 MMMU score calculated?
MMMU is a multimodal 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 Base cost?
Pythia Base costs $0.99 per million input tokens and $4.42 per million output tokens.