Coding · Stability AI

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

StableLM 2 Instruct scores 69.5 on HumanEval, placing it #404 of 600 models in the index. The benchmark average is 74.0 and the leader is GPT-5.2 Pro at 96.8.

Score
69.5
0–100 scale
Rank
#404
of 600
Percentile
33th
within the index
Benchmark avg
74.0
all models
Leader
96.8
GPT-5.2 Pro
Gap to leader
27.3
points

Score distribution

The chart shows the top 10 models on HumanEval, with StableLM 2 Instruct 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 Instruct sits at #404 of 600. The leader, GPT-5.2 Pro, scores 96.8, so the gap to the top is 27.3 points. The median model in this index scores 77.4, which puts StableLM 2 Instruct below the midpoint.

Stability AI models average 58.8 on this benchmark. StableLM 2 Instruct is 10.7 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 Instruct is 2.9 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 69.5 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 $1.93 per million input tokens, StableLM 2 Instruct 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
StableLM 2 Chat Stability AI 8192 $1.79 64.6
Embed 4 Max Cohere 8192 $5.68 66.1
Sonar Pro Nano Perplexity 32768 $5.50 66.1
SmolLM3 Hugging Face 8192 $1.71 63.1
StableLM 2 Instruct Stability AI 16384 $1.93 65.2
ERNIE 4.5 Nano Baidu 32768 $6.01 65.6
Embed 4 Cohere 32768 $4.79 63.8

Other benchmarks for StableLM 2 Instruct

BenchmarkScoreRankPercentileRelative
MMLU-Pro 69.9 396 34th
GPQA Diamond 62.2 389 35th
SWE-bench Verified 54.5 389 35th
MATH-500 67.7 403 33th
AIME 2025 53.9 425 29th
LiveCodeBench 55.9 398 34th
IFEval 72.9 418 30th
TruthfulQA 70.0 400 33th
HellaSwag 77.5 408 32th
MMMU 63.0 399 34th
Arena Elo 1301.8 415 31th

FAQ

What score does StableLM 2 Instruct get on HumanEval?

StableLM 2 Instruct scores 69.5 on HumanEval in this index. The benchmark average is 74.0 and the top score is 96.8.

How does StableLM 2 Instruct rank on HumanEval?

It ranks #404 of 600 models, in the 33rd percentile. The leader is GPT-5.2 Pro at 96.8.

Is StableLM 2 Instruct 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 Instruct cost?

StableLM 2 Instruct costs $1.93 per million input tokens and $8.75 per million output tokens.

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