Knowledge · EleutherAI

Pythia Chat on MMLU-Pro: score, rank and what it means

Pythia Chat scores 63.5 on MMLU-Pro, placing it #483 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
63.5
0–100 scale
Rank
#483
of 600
Percentile
20th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
28.1
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with Pythia Chat highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 91.6
GPT-5.1 Max 91.3
Claude Opus 4.5 Pro 91.2
Claude Opus 4.5 Reasoning 90.7
Gemini 3 Pro Reasoning 90.1
GPT-5.1 Reasoning 90.0
GPT-5.2 89.9
Claude Opus 4.5 Max 89.5
GPT-5.2 Vision 89.5
Gemini 3 Pro Max 89.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg 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 Chat sits at #483 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 28.1 points. The median model in this index scores 76.1, which puts Pythia Chat below the midpoint.

EleutherAI models average 58.0 on this benchmark. Pythia Chat is 5.5 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 Chat is 8.6 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 $1.31 per million input tokens, Pythia Chat 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.

ModelProviderContextInput / 1MAvg score
Llama 3.1 Turbo 8B Together AI 32768 $1.16 58.8
SmolLM3 Base Hugging Face 16384 $1.38 60.4
Llama 3 Baseten 8B Baseten 4096 $1.02 57.0
Llama 3 DeepInfra 7B DeepInfra 16384 $0.95 55.6
Pythia Chat EleutherAI 4096 $1.31 59.1
Llama 4 Scout 7B Meta AI 32768 $1.30 60.0
DeepSeek-Coder 8B DeepSeek 32768 $1.26 58.7

Other benchmarks for Pythia Chat

BenchmarkScoreRankPercentileRelative
GPQA Diamond 55.6 456 24th
SWE-bench Verified 45.6 458 24th
HumanEval 61.9 470 22th
MATH-500 59.3 474 21th
AIME 2025 50.8 454 24th
LiveCodeBench 45.1 498 17th
IFEval 69.6 468 22th
TruthfulQA 66.2 442 26th
HellaSwag 72.5 487 19th
MMMU 60.1 428 29th
Arena Elo 1271.0 456 24th

FAQ

What score does Pythia Chat get on MMLU-Pro?

Pythia Chat scores 63.5 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does Pythia Chat rank on MMLU-Pro?

It ranks #483 of 600 models, in the 20th percentile. The leader is GPT-5.2 Pro at 91.6.

Is Pythia Chat 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 Chat cost?

Pythia Chat costs $1.31 per million input tokens and $5.35 per million output tokens.

Related