Coding · Microsoft

Phi-3.5 1.5B on HumanEval: score, rank and what it means

Phi-3.5 1.5B scores 48.9 on HumanEval, placing it #582 of 600 models in the index. The benchmark average is 74.0 and the leader is GPT-5.2 Pro at 96.8.

Score
48.9
0–100 scale
Rank
#582
of 600
Percentile
3th
within the index
Benchmark avg
74.0
all models
Leader
96.8
GPT-5.2 Pro
Gap to leader
47.9
points

Score distribution

The chart shows the top 10 models on HumanEval, with Phi-3.5 1.5B 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 1.5B sits at #582 of 600. The leader, GPT-5.2 Pro, scores 96.8, so the gap to the top is 47.9 points. The median model in this index scores 77.4, which puts Phi-3.5 1.5B below the midpoint.

Microsoft models average 66.6 on this benchmark. Phi-3.5 1.5B is 17.7 points below that provider line, so it is a weaker result than the average Microsoft model.

Among small open-weight models, the average is 56.7. Phi-3.5 1.5B is 7.8 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 48.9 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 $0.25 per million input tokens, Phi-3.5 1.5B 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
Llama 3 Lambda 1.5B Lambda 16384 $0.46 48.4
Llama 3 Hyperbolic 1.5B Hyperbolic 32768 $0.45 48.4
Yi-Large 1.5B 01.AI 8192 $0.42 46.8
SmolLM3 8B Hugging Face 32768 $0.21 44.0
Phi-3.5 1.5B Microsoft 32768 $0.25 44.5
DBRX 1.5B Databricks 16384 $0.32 47.0
OLMo 2 1.5B Allen Institute for AI 16384 $0.28 44.0

Other benchmarks for Phi-3.5 1.5B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 51.3 587 2th
GPQA Diamond 38.3 591 2th
SWE-bench Verified 27.8 585 3th
MATH-500 43.5 585 3th
AIME 2025 32.8 577 4th
LiveCodeBench 27.7 588 2th
IFEval 58.8 579 4th
TruthfulQA 53.7 580 3th
HellaSwag 65.1 583 3th
MMMU 41.9 589 2th
Arena Elo 1145.1 585 3th

FAQ

What score does Phi-3.5 1.5B get on HumanEval?

Phi-3.5 1.5B scores 48.9 on HumanEval in this index. The benchmark average is 74.0 and the top score is 96.8.

How does Phi-3.5 1.5B rank on HumanEval?

It ranks #582 of 600 models, in the 3rd percentile. The leader is GPT-5.2 Pro at 96.8.

Is Phi-3.5 1.5B 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 1.5B cost?

Phi-3.5 1.5B costs $0.25 per million input tokens and $1.05 per million output tokens.

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