Mathematics · Microsoft

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

Phi-3.5 Instruct scores 74.6 on MATH-500, placing it #338 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
74.6
0–100 scale
Rank
#338
of 600
Percentile
44th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
22.1
points

Score distribution

The chart shows the top 10 models on MATH-500, with Phi-3.5 Instruct 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 Instruct sits at #338 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 22.1 points. The median model in this index scores 76.0, which puts Phi-3.5 Instruct below the midpoint.

Microsoft models average 64.4 on this benchmark. Phi-3.5 Instruct is 10.2 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 Instruct is 3.8 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 74.6 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 $2.67 per million input tokens, Phi-3.5 Instruct 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 Groq Chat Groq 8192 $3.09 72.0
Auto Reasoning OpenRouter 65536 $8.39 71.5
Claude 3.7 Sonnet Mini Anthropic 32768 $9.74 73.0
Firefunction Pro Fireworks AI 16384 $9.05 72.9
Phi-3.5 Instruct Microsoft 16384 $2.67 70.1
o3 Nano OpenAI 32768 $7.78 70.6
Arctic Instruct Snowflake 65536 $2.83 70.6

Other benchmarks for Phi-3.5 Instruct

BenchmarkScoreRankPercentileRelative
MMLU-Pro 74.9 338 44th
GPQA Diamond 65.5 352 41th
SWE-bench Verified 56.1 376 37th
HumanEval 72.1 378 37th
AIME 2025 66.6 323 46th
LiveCodeBench 59.6 373 38th
IFEval 79.2 353 41th
TruthfulQA 75.3 326 46th
HellaSwag 82.2 343 43th
MMMU 65.3 379 37th
Arena Elo 1346.8 369 39th

FAQ

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

Phi-3.5 Instruct scores 74.6 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

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

It ranks #338 of 600 models, in the 44th percentile. The leader is GPT-5.2 Max at 96.7.

Is Phi-3.5 Instruct 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 Instruct cost?

Phi-3.5 Instruct costs $2.67 per million input tokens and $14.62 per million output tokens.

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