Pythia Instruct on MMLU-Pro: score, rank and what it means
Pythia Instruct scores 65.3 on MMLU-Pro, placing it #448 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.
Score distribution
The chart shows the top 10 models on MMLU-Pro, with Pythia Instruct highlighted. Longer bars mean higher scores.
Top 10 leaderboard
| # | Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|---|
| 1 | GPT-5.2 Pro | OpenAI | 2000000 | $21.32 | 89.6 |
| 2 | GPT-5.1 Max | OpenAI | 2000000 | $20.50 | 87.9 |
| 3 | Claude Opus 4.5 Pro | Anthropic | 200000 | $20.98 | 89.1 |
| 4 | Claude Opus 4.5 Reasoning | Anthropic | 2000000 | $20.91 | 88.2 |
| 5 | Gemini 3 Pro Reasoning | Google DeepMind | 200000 | $19.69 | 87.5 |
| 6 | GPT-5.1 Reasoning | OpenAI | 400000 | $20.27 | 88.3 |
| 7 | GPT-5.2 | OpenAI | 2000000 | $19.71 | 88.0 |
| 8 | Claude Opus 4.5 Max | Anthropic | 1000000 | $20.90 | 87.8 |
| 9 | GPT-5.2 Vision | OpenAI | 1000000 | $19.03 | 87.4 |
| 10 | Gemini 3 Pro Max | Google DeepMind | 2000000 | $20.57 | 87.9 |
What this score means
On MMLU-Pro, Pythia Instruct sits at #448 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 26.3 points. The median model in this index scores 76.1, which puts Pythia Instruct below the midpoint.
EleutherAI models average 58.0 on this benchmark. Pythia Instruct is 7.3 points above that provider line, so it is a stronger result than the average EleutherAI model.
Among open-weight models, the average is 72.1. Pythia Instruct is 6.8 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 65.3 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 $1.41 per million input tokens, Pythia Instruct is below the median input price of $4.00 across the 600 models scored on MMLU-Pro. 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 |
|---|---|---|---|---|
| Mistral Large 3 7B | Mistral AI | 32768 | $1.44 | 61.1 |
| Llama 3.1 8B | Meta AI | 8192 | $1.15 | 58.7 |
| MiniMax-M2 8B | MiniMax | 32768 | $1.65 | 61.7 |
| Zephyr Base | Hugging Face | 4096 | $1.26 | 59.5 |
| Pythia Instruct | EleutherAI | 8192 | $1.41 | 60.8 |
| Yi-Lightning 8B | 01.AI | 4096 | $1.16 | 59.2 |
| GPT-NeoX Base | EleutherAI | 16384 | $1.22 | 59.7 |
Other benchmarks for Pythia Instruct
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| GPQA Diamond | 58.3 | 424 | 29th | |
| SWE-bench Verified | 47.1 | 445 | 26th | |
| HumanEval | 66.3 | 427 | 29th | |
| MATH-500 | 63.5 | 429 | 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 MMLU-Pro?
Pythia Instruct scores 65.3 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.
How does Pythia Instruct rank on MMLU-Pro?
It ranks #448 of 600 models, in the 25th percentile. The leader is GPT-5.2 Pro at 91.6.
Is Pythia Instruct good at MMLU-Pro?
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 MMLU-Pro score calculated?
MMLU-Pro is a knowledge 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.