Commonsense · Stability AI

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

StableLM 2 Base scores 74.2 on HellaSwag, placing it #453 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
74.2
0–100 scale
Rank
#453
of 600
Percentile
25th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
21.9
points

Score distribution

The chart shows the top 10 models on HellaSwag, with StableLM 2 Base 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 Base sits at #453 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 21.9 points. The median model in this index scores 83.6, which puts StableLM 2 Base below the midpoint.

Stability AI models average 71.3 on this benchmark. StableLM 2 Base is 2.9 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 Base is 6.0 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 74.2 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 $1.49 per million input tokens, StableLM 2 Base 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 Nano Reka AI 16384 $3.93 61.0
MiniMax-M2 7B MiniMax 8192 $1.44 60.8
Kimi K1.5 7B Moonshot AI 8192 $1.35 59.9
DeepSeek-R1 1.5B DeepSeek 16384 $1.04 56.6
StableLM 2 Base Stability AI 8192 $1.49 61.9
Command R+ 8B Cohere 8192 $1.21 57.7
Yi-Lightning 8B 01.AI 4096 $1.16 59.2

Other benchmarks for StableLM 2 Base

BenchmarkScoreRankPercentileRelative
MMLU-Pro 67.7 421 30th
GPQA Diamond 58.5 421 30th
SWE-bench Verified 44.7 469 22th
HumanEval 67.3 418 30th
MATH-500 63.9 426 29th
AIME 2025 55.9 410 32th
LiveCodeBench 53.3 416 31th
IFEval 70.8 444 26th
TruthfulQA 66.9 432 28th
MMMU 57.4 463 23th
Arena Elo 1288.1 433 28th

FAQ

What score does StableLM 2 Base get on HellaSwag?

StableLM 2 Base scores 74.2 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does StableLM 2 Base rank on HellaSwag?

It ranks #453 of 600 models, in the 25th percentile. The leader is GPT-5.2 Max at 96.1.

Is StableLM 2 Base 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 Base cost?

StableLM 2 Base costs $1.49 per million input tokens and $5.44 per million output tokens.

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