Instruction following · 01.AI

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

Yi-Large scores 81.2 on IFEval, placing it #304 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
81.2
0–100 scale
Rank
#304
of 600
Percentile
49th
within the index
Benchmark avg
78.6
all models
Leader
96.1
Claude Opus 4.5 Pro
Gap to leader
14.9
points

Score distribution

The chart shows the top 10 models on IFEval, with Yi-Large 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 sits at #304 of 600. The leader, Claude Opus 4.5 Pro, scores 96.1, so the gap to the top is 14.9 points. The median model in this index scores 81.2, which puts Yi-Large above the midpoint.

01.AI models average 74.9 on this benchmark. Yi-Large is 6.3 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 is 4.0 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 81.2 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 $3.40 per million input tokens, Yi-Large 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
Mixtral Groq Groq 16384 $3.37 73.1
OLMo 2 Chat Allen Institute for AI 16384 $2.94 70.6
Phi-4 Base Microsoft 32768 $3.15 71.2
QwQ Base Alibaba Cloud 65536 $3.68 74.1
Yi-Large 01.AI 32768 $3.40 73.5
Yi-Large Instruct 01.AI 32768 $3.48 73.4
Firefunction Reasoning Fireworks AI 8192 $9.08 72.5

Other benchmarks for Yi-Large

BenchmarkScoreRankPercentileRelative
MMLU-Pro 77.1 274 54th
GPQA Diamond 70.7 242 60th
SWE-bench Verified 63.7 241 60th
HumanEval 79.4 254 58th
MATH-500 76.2 295 51th
AIME 2025 66.2 327 46th
LiveCodeBench 62.7 338 44th
TruthfulQA 78.0 255 58th
HellaSwag 85.2 237 61th
MMMU 67.8 347 42th
Arena Elo 1389.1 253 58th

FAQ

What score does Yi-Large get on IFEval?

Yi-Large scores 81.2 on IFEval in this index. The benchmark average is 78.6 and the top score is 96.1.

How does Yi-Large rank on IFEval?

It ranks #304 of 600 models, in the 49th percentile. The leader is Claude Opus 4.5 Pro at 96.1.

Is Yi-Large 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 cost?

Yi-Large costs $3.40 per million input tokens and $13.35 per million output tokens.

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