Commonsense · 01.AI

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

Yi-Large Chat scores 82.9 on HellaSwag, placing it #324 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
82.9
0–100 scale
Rank
#324
of 600
Percentile
46th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
13.2
points

Score distribution

The chart shows the top 10 models on HellaSwag, with Yi-Large Chat 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 Chat sits at #324 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 13.2 points. The median model in this index scores 83.6, which puts Yi-Large Chat below the midpoint.

01.AI models average 78.8 on this benchmark. Yi-Large Chat is 4.1 points above that provider line, so it is a stronger result than the average 01.AI model.

Among multimodal models, the average is 86.8. Yi-Large Chat is 3.9 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 82.9 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 $3.49 per million input tokens, Yi-Large Chat 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
Llama 3.3 Base Meta AI 32768 $3.63 74.0
Reka Flash Reka AI 128000 $9.95 74.1
Yi-Large Base 01.AI 16384 $2.78 70.3
Phi-3.5 Microsoft 16384 $2.81 70.9
Yi-Large Chat 01.AI 65536 $3.49 73.5
ERNIE 4.0 Mini Baidu 32768 $7.11 68.8
Mixtral Mistral AI 65536 $3.48 73.7

Other benchmarks for Yi-Large Chat

BenchmarkScoreRankPercentileRelative
MMLU-Pro 75.7 314 48th
GPQA Diamond 69.0 297 51th
SWE-bench Verified 59.3 338 44th
HumanEval 79.5 249 59th
MATH-500 76.1 297 51th
AIME 2025 71.0 238 60th
LiveCodeBench 62.7 339 44th
IFEval 82.4 262 56th
TruthfulQA 78.4 242 60th
MMMU 71.2 269 55th
Arena Elo 1386.2 262 56th

FAQ

What score does Yi-Large Chat get on HellaSwag?

Yi-Large Chat scores 82.9 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does Yi-Large Chat rank on HellaSwag?

It ranks #324 of 600 models, in the 46th percentile. The leader is GPT-5.2 Max at 96.1.

Is Yi-Large Chat 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 Chat cost?

Yi-Large Chat costs $3.49 per million input tokens and $13.97 per million output tokens.

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