Coding · Microsoft

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

Phi-3.5 scores 59.8 on LiveCodeBench, placing it #371 of 600 models in the index. The benchmark average is 61.0 and the leader is Claude Sonnet 4.5 Reasoning at 85.1.

Score
59.8
0–100 scale
Rank
#371
of 600
Percentile
38th
within the index
Benchmark avg
61.0
all models
Leader
85.1
Claude Sonnet 4.5 Reasoning
Gap to leader
25.3
points

Score distribution

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

Claude Sonnet 4.5 Reasoning 85.1
Grok 4 Reasoning 85.1
Claude Opus 4.5 85.0
GPT-5.2 Max 84.8
Grok 4 Turbo 84.7
GPT-5.1 Turbo 84.6
GPT-5.2 Pro 84.6
GPT-5.2 Reasoning 84.6
Claude Opus 4.5 Pro 84.1
Gemini 3 Pro Max 83.6

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
2 Grok 4 Reasoning xAI 2000000 $19.67 87.8
3 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
4 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
5 Grok 4 Turbo xAI 1000000 $19.21 86.7
6 GPT-5.1 Turbo OpenAI 2000000 $19.19 86.1
7 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
8 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
9 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
10 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9

What this score means

On LiveCodeBench, Phi-3.5 sits at #371 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 25.3 points. The median model in this index scores 64.7, which puts Phi-3.5 below the midpoint.

Microsoft models average 52.1 on this benchmark. Phi-3.5 is 7.7 points above that provider line, so it is a stronger result than the average Microsoft model.

Among open-weight models, the average is 59.1. Phi-3.5 is 0.7 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 59.8 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 LiveCodeBench. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Command A Mini Cohere 8192 $8.12 71.0
Auto Max OpenRouter 8192 $8.41 71.2
Claude Haiku 4.5 Nano Anthropic 8192 $6.47 68.7
OLMo 2 Allen Institute for AI 65536 $2.99 71.0
Phi-3.5 Microsoft 16384 $2.81 70.9
Claude 3.7 Sonnet Nano Anthropic 65536 $6.93 68.9
Phi-3.5 Instruct Microsoft 16384 $2.67 70.1

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
HumanEval 76.2 327 46th
MATH-500 75.4 316 47th
AIME 2025 60.6 383 36th
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 LiveCodeBench?

Phi-3.5 scores 59.8 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.

How does Phi-3.5 rank on LiveCodeBench?

It ranks #371 of 600 models, in the 38th percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.

Is Phi-3.5 good at LiveCodeBench?

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 LiveCodeBench score calculated?

LiveCodeBench 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.

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