Coding · 01.AI

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

Yi-Large Chat scores 79.5 on HumanEval, placing it #249 of 600 models in the index. The benchmark average is 74.0 and the leader is GPT-5.2 Pro at 96.8.

Score
79.5
0–100 scale
Rank
#249
of 600
Percentile
59th
within the index
Benchmark avg
74.0
all models
Leader
96.8
GPT-5.2 Pro
Gap to leader
17.3
points

Score distribution

The chart shows the top 10 models on HumanEval, with Yi-Large Chat highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 96.8
Gemini 3 Pro Pro 95.0
o4 Max 94.6
Grok 4 Reasoning 93.8
Claude Opus 4.5 93.7
GPT-5.2 Max 93.6
Claude Opus 4.5 Pro 93.4
Grok 4 Max 93.4
GPT-5.2 Turbo 93.2
GPT-5.1 Reasoning 92.9

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 Gemini 3 Pro Pro Google DeepMind 200000 $19.80 87.3
3 o4 Max OpenAI 2000000 $19.51 86.2
4 Grok 4 Reasoning xAI 2000000 $19.67 87.8
5 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
6 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
7 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
8 Grok 4 Max xAI 2000000 $19.70 86.6
9 GPT-5.2 Turbo OpenAI 1000000 $20.73 87.4
10 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3

What this score means

On HumanEval, Yi-Large Chat sits at #249 of 600. The leader, GPT-5.2 Pro, scores 96.8, so the gap to the top is 17.3 points. The median model in this index scores 77.4, which puts Yi-Large Chat above the midpoint.

01.AI models average 69.1 on this benchmark. Yi-Large Chat is 10.4 points above that provider line, so it is a stronger result than the average 01.AI model.

Among multimodal models, the average is 82.2. Yi-Large Chat 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 79.5 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 $3.49 per million input tokens, Yi-Large Chat is below the median input price of $4.00 across the 600 models scored on HumanEval. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Llama 3 Replicate Chat Replicate 200000 $3.74 74.7
Llama 3.3 Groq Instruct Groq 65536 $4.08 76.7
Llama 3 Anyscale Chat Anyscale 65536 $3.67 74.6
Llama 3 Modal Instruct Modal 128000 $3.84 75.2
Yi-Large Chat 01.AI 65536 $3.49 73.5
Command R+ Cohere 32768 $3.96 76.3
Llama 3 Hyperbolic Instruct Hyperbolic 200000 $3.79 76.2

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
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
HellaSwag 82.9 324 46th
MMMU 71.2 269 55th
Arena Elo 1386.2 262 56th

FAQ

What score does Yi-Large Chat get on HumanEval?

Yi-Large Chat scores 79.5 on HumanEval in this index. The benchmark average is 74.0 and the top score is 96.8.

How does Yi-Large Chat rank on HumanEval?

It ranks #249 of 600 models, in the 59th percentile. The leader is GPT-5.2 Pro at 96.8.

Is Yi-Large Chat good at HumanEval?

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 HumanEval score calculated?

HumanEval is a coding 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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