Commonsense · 01.AI

Yi-Large 1.5B on HellaSwag: score, rank and what it means

Yi-Large 1.5B scores 66.7 on HellaSwag, placing it #570 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
66.7
0–100 scale
Rank
#570
of 600
Percentile
5th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
29.4
points

Score distribution

The chart shows the top 10 models on HellaSwag, with Yi-Large 1.5B 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, Yi-Large 1.5B sits at #570 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 29.4 points. The median model in this index scores 83.6, which puts Yi-Large 1.5B below the midpoint.

01.AI models average 78.8 on this benchmark. Yi-Large 1.5B is 12.1 points below that provider line, so it is a weaker result than the average 01.AI model.

Among small open-weight models, the average is 70.2. Yi-Large 1.5B is 3.5 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 66.7 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 $0.42 per million input tokens, Yi-Large 1.5B 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
Hunyuan-Large 1.5B Tencent 8192 $0.54 50.5
Llama 3 Novita 1.5B Novita AI 4096 $0.41 49.1
Llama 3.1 1.5B Meta AI 4096 $0.53 50.7
StableLM 2 8B Stability AI 32768 $0.38 47.0
Yi-Large 1.5B 01.AI 8192 $0.42 46.8
Phi-3.5 8B Microsoft 16384 $0.59 51.2
Llama 3.3 Groq 1.5B Groq 4096 $0.46 50.0

Other benchmarks for Yi-Large 1.5B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 52.3 585 3th
GPQA Diamond 43.4 576 4th
SWE-bench Verified 33.3 568 5th
HumanEval 49.1 580 3th
MATH-500 45.0 577 4th
AIME 2025 30.0 583 3th
LiveCodeBench 35.8 565 6th
IFEval 59.6 576 4th
TruthfulQA 55.6 572 5th
MMMU 43.8 583 3th
Arena Elo 1176.6 578 4th

FAQ

What score does Yi-Large 1.5B get on HellaSwag?

Yi-Large 1.5B scores 66.7 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does Yi-Large 1.5B rank on HellaSwag?

It ranks #570 of 600 models, in the 5th percentile. The leader is GPT-5.2 Max at 96.1.

Is Yi-Large 1.5B 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 Yi-Large 1.5B cost?

Yi-Large 1.5B costs $0.42 per million input tokens and $2.13 per million output tokens.

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