Coding · Stability AI

StableLM 2 on HumanEval: score, rank and what it means

StableLM 2 scores 70.0 on HumanEval, placing it #394 of 600 models in the index. The benchmark average is 74.0 and the leader is GPT-5.2 Pro at 96.8.

Score
70.0
0–100 scale
Rank
#394
of 600
Percentile
34th
within the index
Benchmark avg
74.0
all models
Leader
96.8
GPT-5.2 Pro
Gap to leader
26.8
points

Score distribution

The chart shows the top 10 models on HumanEval, with StableLM 2 highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 96.8
Gemini 3 Pro Pro 95.0
o4 Max 94.6
Grok 4 Reasoning 93.8
Claude Opus 4.5 93.7
GPT-5.2 Max 93.6
Claude Opus 4.5 Pro 93.4
Grok 4 Max 93.4
GPT-5.2 Turbo 93.2
GPT-5.1 Reasoning 92.9

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 Gemini 3 Pro Pro Google DeepMind 200000 $19.80 87.3
3 o4 Max OpenAI 2000000 $19.51 86.2
4 Grok 4 Reasoning xAI 2000000 $19.67 87.8
5 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
6 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
7 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
8 Grok 4 Max xAI 2000000 $19.70 86.6
9 GPT-5.2 Turbo OpenAI 1000000 $20.73 87.4
10 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3

What this score means

On HumanEval, StableLM 2 sits at #394 of 600. The leader, GPT-5.2 Pro, scores 96.8, so the gap to the top is 26.8 points. The median model in this index scores 77.4, which puts StableLM 2 below the midpoint.

Stability AI models average 58.8 on this benchmark. StableLM 2 is 11.2 points above that provider line, so it is a stronger result than the average Stability AI model.

Among open-weight models, the average is 72.4. StableLM 2 is 2.4 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 70.0 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 $1.91 per million input tokens, StableLM 2 is below the median input price of $4.00 across the 600 models scored on HumanEval. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Sonar Mini Perplexity 65536 $6.52 67.9
OLMo 2 Base Allen Institute for AI 65536 $2.39 67.4
Embed 4 Turbo Cohere 4096 $5.13 64.0
Molmo Chat Allen Institute for AI 32768 $2.40 66.7
StableLM 2 Stability AI 8192 $1.91 65.0
Kimi K2 8B Moonshot AI 8192 $1.86 64.7
Molmo Base Allen Institute for AI 4096 $2.02 65.0

Other benchmarks for StableLM 2

BenchmarkScoreRankPercentileRelative
MMLU-Pro 71.4 387 36th
GPQA Diamond 57.9 429 29th
SWE-bench Verified 52.0 407 32th
MATH-500 68.3 397 34th
AIME 2025 56.5 408 32th
LiveCodeBench 55.2 402 33th
IFEval 73.2 413 31th
TruthfulQA 68.7 408 32th
HellaSwag 77.2 413 31th
MMMU 64.2 387 36th
Arena Elo 1294.3 426 29th

FAQ

What score does StableLM 2 get on HumanEval?

StableLM 2 scores 70.0 on HumanEval in this index. The benchmark average is 74.0 and the top score is 96.8.

How does StableLM 2 rank on HumanEval?

It ranks #394 of 600 models, in the 34th percentile. The leader is GPT-5.2 Pro at 96.8.

Is StableLM 2 good at HumanEval?

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 HumanEval score calculated?

HumanEval is a coding 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 cost?

StableLM 2 costs $1.91 per million input tokens and $9.65 per million output tokens.

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