Commonsense · Stability AI

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

StableLM 2 Instruct scores 77.5 on HellaSwag, placing it #408 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
77.5
0–100 scale
Rank
#408
of 600
Percentile
32th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
18.6
points

Score distribution

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

GPT-5.2 Max 96.1
GPT-5.2 Turbo 95.5
GPT-5.2 Pro 95.3
Claude Opus 4.5 Pro 95.2
Claude Sonnet 4.5 Reasoning 95.2
Grok 4 Reasoning 95.2
GPT-5.2 Vision 94.6
Gemini 3 Pro Turbo 94.6
GPT-5.1 Reasoning 94.4
o4 Pro 94.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.2 Turbo OpenAI 1000000 $20.73 87.4
3 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
4 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
5 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
6 Grok 4 Reasoning xAI 2000000 $19.67 87.8
7 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4
8 Gemini 3 Pro Turbo Google DeepMind 400000 $19.62 86.4
9 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
10 o4 Pro OpenAI 1000000 $19.37 87.3

What this score means

On HellaSwag, StableLM 2 Instruct sits at #408 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 18.6 points. The median model in this index scores 83.6, which puts StableLM 2 Instruct below the midpoint.

Stability AI models average 71.3 on this benchmark. StableLM 2 Instruct is 6.2 points above that provider line, so it is a stronger result than the average Stability AI model.

Among open-weight models, the average is 80.2. StableLM 2 Instruct is 2.7 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 77.5 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 HellaSwag. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Reka Flash Mini Reka AI 16384 $5.77 65.5
SmolLM3 Hugging Face 8192 $1.71 63.1
Molmo Base Allen Institute for AI 4096 $2.02 65.0
Fusion Mini OpenRouter 4096 $4.89 63.3
StableLM 2 Instruct Stability AI 16384 $1.93 65.2
DeepSeek-V3.2 8B DeepSeek 32768 $2.02 66.2
ERNIE 4.5 Nano Baidu 32768 $6.01 65.6

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
HumanEval 69.5 404 33th
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
MMMU 63.0 399 34th
Arena Elo 1301.8 415 31th

FAQ

What score does StableLM 2 Instruct get on HellaSwag?

StableLM 2 Instruct scores 77.5 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does StableLM 2 Instruct rank on HellaSwag?

It ranks #408 of 600 models, in the 32nd percentile. The leader is GPT-5.2 Max at 96.1.

Is StableLM 2 Instruct good at HellaSwag?

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 HellaSwag score calculated?

HellaSwag is a commonsense 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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