Instruction following · Anthropic

Claude Haiku 4.5 Pro on IFEval: score, rank and what it means

Claude Haiku 4.5 Pro scores 90.1 on IFEval, placing it #70 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
90.1
0–100 scale
Rank
#70
of 600
Percentile
88th
within the index
Benchmark avg
78.6
all models
Leader
96.1
Claude Opus 4.5 Pro
Gap to leader
6.0
points

Score distribution

The chart shows the top 10 models on IFEval, with Claude Haiku 4.5 Pro 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, Claude Haiku 4.5 Pro sits at #70 of 600. The leader, Claude Opus 4.5 Pro, scores 96.1, so the gap to the top is 6.0 points. The median model in this index scores 81.2, which puts Claude Haiku 4.5 Pro above the midpoint.

Anthropic models average 88.3 on this benchmark. Claude Haiku 4.5 Pro is 1.8 points above that provider line, so it is a stronger result than the average Anthropic model.

Among multimodal models, the average is 85.2. Claude Haiku 4.5 Pro is 4.9 points above that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 90.1 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 $15.07 per million input tokens, Claude Haiku 4.5 Pro is above 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 2.5 Pro Vision Google DeepMind 200000 $14.91 82.0
Gemini 3 Flash Reasoning Google DeepMind 128000 $17.05 83.7
Grok 3 Reasoning xAI 200000 $16.07 82.9
Claude 3.7 Sonnet Reasoning Anthropic 128000 $16.30 83.7
Claude Haiku 4.5 Pro Anthropic 1000000 $15.07 80.8
Claude 3.7 Sonnet Max Anthropic 128000 $16.88 83.7
Claude Haiku 4.5 Max Anthropic 200000 $15.98 83.8

Other benchmarks for Claude Haiku 4.5 Pro

BenchmarkScoreRankPercentileRelative
MMLU-Pro 81.5 133 78th
GPQA Diamond 75.7 128 79th
SWE-bench Verified 70.4 101 83th
HumanEval 86.0 101 83th
MATH-500 83.7 131 78th
AIME 2025 80.1 87 86th
LiveCodeBench 72.4 138 77th
TruthfulQA 84.1 81 87th
HellaSwag 89.3 105 83th
MMMU 75.3 157 74th
Arena Elo 1436.2 105 83th

FAQ

What score does Claude Haiku 4.5 Pro get on IFEval?

Claude Haiku 4.5 Pro scores 90.1 on IFEval in this index. The benchmark average is 78.6 and the top score is 96.1.

How does Claude Haiku 4.5 Pro rank on IFEval?

It ranks #70 of 600 models, in the 88th percentile. The leader is Claude Opus 4.5 Pro at 96.1.

Is Claude Haiku 4.5 Pro 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 Claude Haiku 4.5 Pro cost?

Claude Haiku 4.5 Pro costs $15.07 per million input tokens and $73.96 per million output tokens.

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