Coding · 01.AI

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

Yi-Large Chat scores 62.7 on LiveCodeBench, placing it #339 of 600 models in the index. The benchmark average is 61.0 and the leader is Claude Sonnet 4.5 Reasoning at 85.1.

Score
62.7
0–100 scale
Rank
#339
of 600
Percentile
44th
within the index
Benchmark avg
61.0
all models
Leader
85.1
Claude Sonnet 4.5 Reasoning
Gap to leader
22.4
points

Score distribution

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

Claude Sonnet 4.5 Reasoning 85.1
Grok 4 Reasoning 85.1
Claude Opus 4.5 85.0
GPT-5.2 Max 84.8
Grok 4 Turbo 84.7
GPT-5.1 Turbo 84.6
GPT-5.2 Pro 84.6
GPT-5.2 Reasoning 84.6
Claude Opus 4.5 Pro 84.1
Gemini 3 Pro Max 83.6

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
2 Grok 4 Reasoning xAI 2000000 $19.67 87.8
3 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
4 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
5 Grok 4 Turbo xAI 1000000 $19.21 86.7
6 GPT-5.1 Turbo OpenAI 2000000 $19.19 86.1
7 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
8 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
9 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
10 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9

What this score means

On LiveCodeBench, Yi-Large Chat sits at #339 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 22.4 points. The median model in this index scores 64.7, which puts Yi-Large Chat below the midpoint.

01.AI models average 55.4 on this benchmark. Yi-Large Chat is 7.3 points above that provider line, so it is a stronger result than the average 01.AI model.

Among multimodal models, the average is 70.3. Yi-Large Chat is 7.6 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 62.7 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 $3.49 per million input tokens, Yi-Large Chat is below the median input price of $4.00 across the 600 models scored on LiveCodeBench. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Llama 3 Baseten Baseten 128000 $3.62 74.9
ERNIE 4.5 Mini Baidu 32768 $8.62 71.0
Auto Pro OpenRouter 8192 $8.41 71.2
Yi-Large 01.AI 32768 $3.40 73.5
Yi-Large Chat 01.AI 65536 $3.49 73.5
Phi-3.5 Chat Microsoft 16384 $2.64 69.0
Llama 3 Hyperbolic Base Hyperbolic 32768 $3.02 71.1

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
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 LiveCodeBench?

Yi-Large Chat scores 62.7 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.

How does Yi-Large Chat rank on LiveCodeBench?

It ranks #339 of 600 models, in the 44th percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.

Is Yi-Large Chat good at LiveCodeBench?

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 LiveCodeBench score calculated?

LiveCodeBench 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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