Mathematics · Microsoft

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

Phi-3.5 Base scores 71.6 on MATH-500, placing it #373 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
71.6
0–100 scale
Rank
#373
of 600
Percentile
38th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
25.1
points

Score distribution

The chart shows the top 10 models on MATH-500, with Phi-3.5 Base 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 Base sits at #373 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 25.1 points. The median model in this index scores 76.0, which puts Phi-3.5 Base below the midpoint.

Microsoft models average 64.4 on this benchmark. Phi-3.5 Base is 7.2 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 Base is 0.8 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 71.6 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 $2.24 per million input tokens, Phi-3.5 Base 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
Claude Haiku 4.5 Nano Anthropic 8192 $6.47 68.7
Arctic Base Snowflake 32768 $2.27 67.5
ERNIE 4.0 Mini Baidu 32768 $7.11 68.8
Grok 3 Nano xAI 8192 $7.12 67.8
Phi-3.5 Base Microsoft 65536 $2.24 66.6
Arctic Chat Snowflake 16384 $2.70 69.8
Auto Pro OpenRouter 8192 $8.41 71.2

Other benchmarks for Phi-3.5 Base

BenchmarkScoreRankPercentileRelative
MMLU-Pro 72.4 379 37th
GPQA Diamond 60.3 402 33th
SWE-bench Verified 51.6 409 32th
HumanEval 73.1 371 38th
AIME 2025 59.7 389 35th
LiveCodeBench 55.2 401 33th
IFEval 74.2 404 33th
TruthfulQA 73.0 370 38th
HellaSwag 79.5 389 35th
MMMU 61.7 412 31th
Arena Elo 1315.0 400 33th

FAQ

What score does Phi-3.5 Base get on MATH-500?

Phi-3.5 Base scores 71.6 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Phi-3.5 Base rank on MATH-500?

It ranks #373 of 600 models, in the 38th percentile. The leader is GPT-5.2 Max at 96.7.

Is Phi-3.5 Base 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 Base cost?

Phi-3.5 Base costs $2.24 per million input tokens and $10.25 per million output tokens.

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