Knowledge · Stability AI

StableLM 2 Chat on MMLU-Pro: score, rank and what it means

StableLM 2 Chat scores 66.4 on MMLU-Pro, placing it #436 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
66.4
0–100 scale
Rank
#436
of 600
Percentile
27th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
25.2
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with StableLM 2 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, StableLM 2 Chat sits at #436 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 25.2 points. The median model in this index scores 76.1, which puts StableLM 2 Chat below the midpoint.

Stability AI models average 61.2 on this benchmark. StableLM 2 Chat is 5.2 points above that provider line, so it is a stronger result than the average Stability AI model.

Among open-weight models, the average is 72.1. StableLM 2 Chat is 5.7 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 66.4 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 $1.79 per million input tokens, StableLM 2 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
Qwen3 8B Alibaba Cloud 8192 $1.66 61.9
Nova Lite Nano Amazon 8192 $3.29 59.5
Qwen3-Coder 7B Alibaba Cloud 32768 $1.24 59.6
Reka Flash Nano Reka AI 16384 $3.93 61.0
StableLM 2 Chat Stability AI 8192 $1.79 64.6
Kimi K1.5 7B Moonshot AI 8192 $1.35 59.9
Hunyuan-Turbo Nano Tencent 32768 $4.65 62.7

Other benchmarks for StableLM 2 Chat

BenchmarkScoreRankPercentileRelative
GPQA Diamond 61.8 392 35th
SWE-bench Verified 51.6 410 32th
HumanEval 69.7 400 33th
MATH-500 68.0 401 33th
AIME 2025 52.6 439 27th
LiveCodeBench 55.7 399 34th
IFEval 74.9 400 33th
TruthfulQA 70.1 399 34th
HellaSwag 78.7 396 34th
MMMU 61.0 421 30th
Arena Elo 1297.5 425 29th

FAQ

What score does StableLM 2 Chat get on MMLU-Pro?

StableLM 2 Chat scores 66.4 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does StableLM 2 Chat rank on MMLU-Pro?

It ranks #436 of 600 models, in the 27th percentile. The leader is GPT-5.2 Pro at 91.6.

Is StableLM 2 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 StableLM 2 Chat cost?

StableLM 2 Chat costs $1.79 per million input tokens and $9.72 per million output tokens.

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