Commonsense · 01.AI

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

Yi-Large Instruct scores 84.3 on HellaSwag, placing it #269 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
84.3
0–100 scale
Rank
#269
of 600
Percentile
55th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
11.8
points

Score distribution

The chart shows the top 10 models on HellaSwag, with Yi-Large 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, Yi-Large Instruct sits at #269 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 11.8 points. The median model in this index scores 83.6, which puts Yi-Large Instruct above the midpoint.

01.AI models average 78.8 on this benchmark. Yi-Large Instruct is 5.5 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 Instruct is 2.5 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 84.3 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 $3.48 per million input tokens, Yi-Large 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
Llama 3 Novita Novita AI 128000 $3.70 74.4
Llama 3 Novita Instruct Novita AI 32768 $3.94 75.6
Llama 3.1 Turbo Base Together AI 16384 $3.30 73.0
Nemotron 4 Chat NVIDIA 65536 $3.99 75.0
Yi-Large Instruct 01.AI 32768 $3.48 73.4
Llama 3 Baseten Baseten 128000 $3.62 74.9
Llama 3 Baseten Chat Baseten 200000 $3.55 73.2

Other benchmarks for Yi-Large Instruct

BenchmarkScoreRankPercentileRelative
MMLU-Pro 77.8 252 58th
GPQA Diamond 70.0 265 56th
SWE-bench Verified 60.4 320 47th
HumanEval 77.1 307 49th
MATH-500 78.2 254 58th
AIME 2025 64.9 339 44th
LiveCodeBench 65.9 277 54th
IFEval 81.2 305 49th
TruthfulQA 74.5 342 43th
MMMU 73.2 214 64th
Arena Elo 1390.6 248 59th

FAQ

What score does Yi-Large Instruct get on HellaSwag?

Yi-Large Instruct scores 84.3 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does Yi-Large Instruct rank on HellaSwag?

It ranks #269 of 600 models, in the 55th percentile. The leader is GPT-5.2 Max at 96.1.

Is Yi-Large Instruct good at HellaSwag?

Yes, relative to the index: it is above the median and inside the top half of scores. 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 Instruct cost?

Yi-Large Instruct costs $3.48 per million input tokens and $13.46 per million output tokens.

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