Instruction following · Microsoft

Phi-3.5 7B on IFEval: score, rank and what it means

Phi-3.5 7B scores 61.5 on IFEval, placing it #561 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
61.5
0–100 scale
Rank
#561
of 600
Percentile
7th
within the index
Benchmark avg
78.6
all models
Leader
96.1
Claude Opus 4.5 Pro
Gap to leader
34.6
points

Score distribution

The chart shows the top 10 models on IFEval, with Phi-3.5 7B 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, Phi-3.5 7B sits at #561 of 600. The leader, Claude Opus 4.5 Pro, scores 96.1, so the gap to the top is 34.6 points. The median model in this index scores 81.2, which puts Phi-3.5 7B below the midpoint.

Microsoft models average 72.4 on this benchmark. Phi-3.5 7B is 10.9 points below that provider line, so it is a weaker result than the average Microsoft model.

Among small open-weight models, the average is 64.9. Phi-3.5 7B is 3.4 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 61.5 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 $0.50 per million input tokens, Phi-3.5 7B 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
DeepSeek-Coder 1.5B DeepSeek 16384 $0.58 51.0
Llama 3.1 1.5B Meta AI 4096 $0.53 50.7
Mixtral 1.5B Mistral AI 16384 $0.36 47.7
Llama 3.1 Cerebras 1.5B Cerebras 4096 $0.48 50.2
Phi-3.5 7B Microsoft 4096 $0.50 50.5
Molmo 7B Allen Institute for AI 32768 $0.42 49.3
Llama 3.3 Groq 1.5B Groq 4096 $0.46 50.0

Other benchmarks for Phi-3.5 7B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 59.3 534 11th
GPQA Diamond 47.6 542 10th
SWE-bench Verified 33.2 570 5th
HumanEval 54.5 547 9th
MATH-500 51.8 544 9th
AIME 2025 36.8 557 7th
LiveCodeBench 35.2 569 5th
TruthfulQA 55.0 574 4th
HellaSwag 69.1 546 9th
MMMU 51.1 543 10th
Arena Elo 1190.4 565 6th

FAQ

What score does Phi-3.5 7B get on IFEval?

Phi-3.5 7B scores 61.5 on IFEval in this index. The benchmark average is 78.6 and the top score is 96.1.

How does Phi-3.5 7B rank on IFEval?

It ranks #561 of 600 models, in the 7th percentile. The leader is Claude Opus 4.5 Pro at 96.1.

Is Phi-3.5 7B good at IFEval?

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 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 Phi-3.5 7B cost?

Phi-3.5 7B costs $0.50 per million input tokens and $2.68 per million output tokens.

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