Mathematics · Microsoft

Phi-3.5 on MATH-500: score, rank and what it means

Phi-3.5 scores 75.4 on MATH-500, placing it #316 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
75.4
0–100 scale
Rank
#316
of 600
Percentile
47th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
21.3
points

Score distribution

The chart shows the top 10 models on MATH-500, with Phi-3.5 highlighted. Longer bars mean higher scores.

GPT-5.2 Max 96.7
GPT-5.1 Reasoning 95.9
GPT-5.1 Pro 95.1
o4 Reasoning 94.8
Grok 4 Max 94.6
Grok 4 Reasoning 94.4
Claude Opus 4.5 Max 94.2
Claude Opus 4.5 93.7
Gemini 3 Pro Reasoning 93.3
Claude Opus 4.5 Turbo 93.2

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
3 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
4 o4 Reasoning OpenAI 1000000 $19.69 87.5
5 Grok 4 Max xAI 2000000 $19.70 86.6
6 Grok 4 Reasoning xAI 2000000 $19.67 87.8
7 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
8 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
9 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
10 Claude Opus 4.5 Turbo Anthropic 2000000 $19.57 85.7

What this score means

On MATH-500, Phi-3.5 sits at #316 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 21.3 points. The median model in this index scores 76.0, which puts Phi-3.5 below the midpoint.

Microsoft models average 64.4 on this benchmark. Phi-3.5 is 11.0 points above that provider line, so it is a stronger result than the average Microsoft model.

Among open-weight models, the average is 70.8. Phi-3.5 is 4.6 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 75.4 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 MATH-500. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Mixtral Instruct Mistral AI 65536 $3.35 72.9
Qwen3-Max Nano Alibaba Cloud 65536 $8.31 71.7
Seed-OSS Chat ByteDance 65536 $3.49 74.4
Mixtral Turbo Together AI 65536 $3.20 72.4
Phi-3.5 Microsoft 16384 $2.81 70.9
Command A Mini Cohere 8192 $8.12 71.0
ERNIE 4.5 Mini Baidu 32768 $8.62 71.0

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
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 MATH-500?

Phi-3.5 scores 75.4 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Phi-3.5 rank on MATH-500?

It ranks #316 of 600 models, in the 47th percentile. The leader is GPT-5.2 Max at 96.7.

Is Phi-3.5 good at MATH-500?

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 MATH-500 score calculated?

MATH-500 is a mathematics 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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