Coding · Microsoft

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

Phi-3.5 Chat scores 62.6 on LiveCodeBench, placing it #340 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
62.6
0–100 scale
Rank
#340
of 600
Percentile
43th
within the index
Benchmark avg
61.0
all models
Leader
85.1
Claude Sonnet 4.5 Reasoning
Gap to leader
22.5
points

Score distribution

The chart shows the top 10 models on LiveCodeBench, with Phi-3.5 Chat 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 Chat sits at #340 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 22.5 points. The median model in this index scores 64.7, which puts Phi-3.5 Chat below the midpoint.

Microsoft models average 52.1 on this benchmark. Phi-3.5 Chat is 10.5 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 Chat is 3.5 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 62.6 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 $2.64 per million input tokens, Phi-3.5 Chat 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
ERNIE 4.5 Mini Baidu 32768 $8.62 71.0
Auto Pro OpenRouter 8192 $8.41 71.2
Yi-Large 01.AI 32768 $3.40 73.5
Yi-Large Chat 01.AI 65536 $3.49 73.5
Phi-3.5 Chat Microsoft 16384 $2.64 69.0
Llama 3 Hyperbolic Base Hyperbolic 32768 $3.02 71.1
Mixtral Mistral AI 65536 $3.48 73.7

Other benchmarks for Phi-3.5 Chat

BenchmarkScoreRankPercentileRelative
MMLU-Pro 74.4 345 43th
GPQA Diamond 64.9 362 40th
SWE-bench Verified 56.6 372 38th
HumanEval 71.0 389 35th
MATH-500 69.0 388 35th
AIME 2025 64.6 346 42th
IFEval 79.2 352 41th
TruthfulQA 72.4 377 37th
HellaSwag 80.9 373 38th
MMMU 63.7 393 35th
Arena Elo 1338.0 380 37th

FAQ

What score does Phi-3.5 Chat get on LiveCodeBench?

Phi-3.5 Chat scores 62.6 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.

How does Phi-3.5 Chat rank on LiveCodeBench?

It ranks #340 of 600 models, in the 43rd percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.

Is Phi-3.5 Chat 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 Chat cost?

Phi-3.5 Chat costs $2.64 per million input tokens and $12.13 per million output tokens.

Related