Instruction following · 01.AI

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

Yi-Large Chat scores 82.4 on IFEval, placing it #262 of 600 models in the index. The benchmark average is 78.6 and the leader is Claude Opus 4.5 Pro at 96.1.

Score
82.4
0–100 scale
Rank
#262
of 600
Percentile
56th
within the index
Benchmark avg
78.6
all models
Leader
96.1
Claude Opus 4.5 Pro
Gap to leader
13.7
points

Score distribution

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

Claude Opus 4.5 Pro 96.1
Claude Opus 4.5 Reasoning 95.9
GPT-5.2 Pro 95.6
GPT-5.2 Max 95.2
GPT-5.2 Reasoning 95.0
GPT-5.1 Pro 94.8
Gemini 3 Pro Max 94.7
GPT-5.1 Reasoning 94.6
Claude Opus 4.5 Max 94.5
o4 Reasoning 94.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
2 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
3 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
4 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
5 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
6 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
7 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9
8 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
9 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
10 o4 Reasoning OpenAI 1000000 $19.69 87.5

What this score means

On IFEval, Yi-Large Chat sits at #262 of 600. The leader, Claude Opus 4.5 Pro, scores 96.1, so the gap to the top is 13.7 points. The median model in this index scores 81.2, which puts Yi-Large Chat above the midpoint.

01.AI models average 74.9 on this benchmark. Yi-Large Chat is 7.5 points above that provider line, so it is a stronger result than the average 01.AI model.

Among multimodal models, the average is 85.2. Yi-Large Chat is 2.8 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 82.4 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 IFEval. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Gemini 3 Pro Nano Google DeepMind 8192 $9.11 73.2
DBRX Instruct Databricks 8192 $3.21 72.4
Firefunction Max Fireworks AI 32768 $9.12 73.2
Llama 3 Replicate Chat Replicate 200000 $3.74 74.7
Yi-Large Chat 01.AI 65536 $3.49 73.5
Claude Haiku 4.5 Mini Anthropic 16384 $8.76 71.6
DBRX Databricks 65536 $3.29 73.3

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
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 IFEval?

Yi-Large Chat scores 82.4 on IFEval in this index. The benchmark average is 78.6 and the top score is 96.1.

How does Yi-Large Chat rank on IFEval?

It ranks #262 of 600 models, in the 56th percentile. The leader is Claude Opus 4.5 Pro at 96.1.

Is Yi-Large Chat good at IFEval?

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 IFEval score calculated?

IFEval is a instruction following 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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