Coding · Microsoft

Phi-4 on SWE-bench Verified: score, rank and what it means

Phi-4 scores 66.5 on SWE-bench Verified, placing it #180 of 600 models in the index. The benchmark average is 57.5 and the leader is GPT-5.2 Pro at 81.7.

Score
66.5
0–100 scale
Rank
#180
of 600
Percentile
70th
within the index
Benchmark avg
57.5
all models
Leader
81.7
GPT-5.2 Pro
Gap to leader
15.2
points

Score distribution

The chart shows the top 10 models on SWE-bench Verified, with Phi-4 highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 81.7
Claude Opus 4.5 Pro 81.1
GPT-5.2 Max 80.5
Claude Sonnet 4.5 Max 80.2
GPT-5.2 80.2
GPT-5.1 Pro 80.1
o4 Max 79.8
Claude Sonnet 4.5 Reasoning 79.6
Claude Opus 4.5 Max 79.5
Claude Opus 4.5 Reasoning 79.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
3 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
4 Claude Sonnet 4.5 Max Anthropic 1000000 $19.90 87.2
5 GPT-5.2 OpenAI 2000000 $19.71 88.0
6 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
7 o4 Max OpenAI 2000000 $19.51 86.2
8 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
9 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
10 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2

What this score means

On SWE-bench Verified, Phi-4 sits at #180 of 600. The leader, GPT-5.2 Pro, scores 81.7, so the gap to the top is 15.2 points. The median model in this index scores 61.0, which puts Phi-4 above the midpoint.

Microsoft models average 49.9 on this benchmark. Phi-4 is 16.6 points above that provider line, so it is a stronger result than the average Microsoft model.

Among multimodal models, the average is 66.4. Phi-4 is 0.1 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 66.5 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 $3.96 per million input tokens, Phi-4 is below the median input price of $4.00 across the 600 models scored on SWE-bench Verified. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Qwen3 Base Alibaba Cloud 65536 $4.33 77.4
Llama 4 Maverick Chat Meta AI 128000 $5.09 79.7
ERNIE 4.5 Pro Baidu 1000000 $13.89 80.5
Magistral Mistral AI 200000 $4.75 79.8
Phi-4 Microsoft 200000 $3.96 75.4
GLM-4.5 Zhipu AI 200000 $4.55 78.2
MiniMax-M2 Chat MiniMax 200000 $5.02 80.2

Other benchmarks for Phi-4

BenchmarkScoreRankPercentileRelative
MMLU-Pro 79.5 198 67th
GPQA Diamond 69.4 284 53th
HumanEval 79.4 253 58th
MATH-500 79.0 236 61th
AIME 2025 74.1 180 70th
LiveCodeBench 64.7 303 50th
IFEval 83.0 246 59th
TruthfulQA 76.5 295 51th
HellaSwag 86.3 206 66th
MMMU 71.2 267 56th
Arena Elo 1392.0 240 60th

FAQ

What score does Phi-4 get on SWE-bench Verified?

Phi-4 scores 66.5 on SWE-bench Verified in this index. The benchmark average is 57.5 and the top score is 81.7.

How does Phi-4 rank on SWE-bench Verified?

It ranks #180 of 600 models, in the 70th percentile. The leader is GPT-5.2 Pro at 81.7.

Is Phi-4 good at SWE-bench Verified?

Yes, relative to the index: it is above the median and inside the top half of scores. The result should be read alongside its price and context window.

How is the SWE-bench Verified score calculated?

SWE-bench Verified 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-4 cost?

Phi-4 costs $3.96 per million input tokens and $20.63 per million output tokens.

Related