Coding · Microsoft

Phi-3.5 on HumanEval: score, rank and what it means

Phi-3.5 scores 76.2 on HumanEval, placing it #327 of 600 models in the index. The benchmark average is 74.0 and the leader is GPT-5.2 Pro at 96.8.

Score
76.2
0–100 scale
Rank
#327
of 600
Percentile
46th
within the index
Benchmark avg
74.0
all models
Leader
96.8
GPT-5.2 Pro
Gap to leader
20.6
points

Score distribution

The chart shows the top 10 models on HumanEval, with Phi-3.5 highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 96.8
Gemini 3 Pro Pro 95.0
o4 Max 94.6
Grok 4 Reasoning 93.8
Claude Opus 4.5 93.7
GPT-5.2 Max 93.6
Claude Opus 4.5 Pro 93.4
Grok 4 Max 93.4
GPT-5.2 Turbo 93.2
GPT-5.1 Reasoning 92.9

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 Gemini 3 Pro Pro Google DeepMind 200000 $19.80 87.3
3 o4 Max OpenAI 2000000 $19.51 86.2
4 Grok 4 Reasoning xAI 2000000 $19.67 87.8
5 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
6 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
7 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
8 Grok 4 Max xAI 2000000 $19.70 86.6
9 GPT-5.2 Turbo OpenAI 1000000 $20.73 87.4
10 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3

What this score means

On HumanEval, Phi-3.5 sits at #327 of 600. The leader, GPT-5.2 Pro, scores 96.8, so the gap to the top is 20.6 points. The median model in this index scores 77.4, which puts Phi-3.5 below the midpoint.

Microsoft models average 66.6 on this benchmark. Phi-3.5 is 9.6 points above that provider line, so it is a stronger result than the average Microsoft model.

Among open-weight models, the average is 72.4. Phi-3.5 is 3.8 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 76.2 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 $2.81 per million input tokens, Phi-3.5 is below the median input price of $4.00 across the 600 models scored on HumanEval. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Claude Haiku 4.5 Mini Anthropic 16384 $8.76 71.6
Fusion Turbo OpenRouter 8192 $8.55 71.7
Grok 4 Nano xAI 16384 $8.97 72.7
Llama 3 DeepInfra Base DeepInfra 16384 $2.95 71.8
Phi-3.5 Microsoft 16384 $2.81 70.9
GPT-5.1 Nano OpenAI 32768 $9.56 74.1
DBRX Base Databricks 32768 $2.63 69.1

Other benchmarks for Phi-3.5

BenchmarkScoreRankPercentileRelative
MMLU-Pro 76.1 304 49th
GPQA Diamond 67.0 331 45th
SWE-bench Verified 60.9 308 49th
MATH-500 75.4 316 47th
AIME 2025 60.6 383 36th
LiveCodeBench 59.8 371 38th
IFEval 77.1 377 37th
TruthfulQA 74.8 336 44th
HellaSwag 82.9 323 46th
MMMU 68.8 328 45th
Arena Elo 1356.7 350 42th

FAQ

What score does Phi-3.5 get on HumanEval?

Phi-3.5 scores 76.2 on HumanEval in this index. The benchmark average is 74.0 and the top score is 96.8.

How does Phi-3.5 rank on HumanEval?

It ranks #327 of 600 models, in the 46th percentile. The leader is GPT-5.2 Pro at 96.8.

Is Phi-3.5 good at HumanEval?

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 HumanEval score calculated?

HumanEval 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 Phi-3.5 cost?

Phi-3.5 costs $2.81 per million input tokens and $14.99 per million output tokens.

Related