Coding · Microsoft

Phi-4 7B on SWE-bench Verified: score, rank and what it means

Phi-4 7B scores 44.0 on SWE-bench Verified, placing it #479 of 600 models in the index. The benchmark average is 57.5 and the leader is GPT-5.2 Pro at 81.7.

Score
44.0
0–100 scale
Rank
#479
of 600
Percentile
20th
within the index
Benchmark avg
57.5
all models
Leader
81.7
GPT-5.2 Pro
Gap to leader
37.7
points

Score distribution

The chart shows the top 10 models on SWE-bench Verified, with Phi-4 7B 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 7B sits at #479 of 600. The leader, GPT-5.2 Pro, scores 81.7, so the gap to the top is 37.7 points. The median model in this index scores 61.0, which puts Phi-4 7B below the midpoint.

Microsoft models average 49.9 on this benchmark. Phi-4 7B is 5.9 points below that provider line, so it is a weaker result than the average Microsoft model.

Among small open-weight models, the average is 39.0. Phi-4 7B is 5.0 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 44.0 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 $0.91 per million input tokens, Phi-4 7B 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
Auto Nano OpenRouter 4096 $2.83 57.1
Hunyuan-Large 7B Tencent 32768 $1.08 57.7
Llama 3.1 7B Meta AI 8192 $1.01 57.4
Codestral 7B Mistral AI 32768 $1.05 57.0
Phi-4 7B Microsoft 8192 $0.91 56.8
Command R+ 7B Cohere 8192 $0.95 56.2
Llama 3.1 Turbo 7B Together AI 8192 $0.98 56.4

Other benchmarks for Phi-4 7B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 62.4 498 17th
GPQA Diamond 52.7 492 18th
HumanEval 61.3 479 20th
MATH-500 55.6 514 14th
AIME 2025 48.7 465 23th
LiveCodeBench 43.3 514 14th
IFEval 67.9 491 18th
TruthfulQA 60.2 527 12th
HellaSwag 71.4 514 14th
MMMU 57.1 469 22th
Arena Elo 1241.9 508 15th

FAQ

What score does Phi-4 7B get on SWE-bench Verified?

Phi-4 7B scores 44.0 on SWE-bench Verified in this index. The benchmark average is 57.5 and the top score is 81.7.

How does Phi-4 7B rank on SWE-bench Verified?

It ranks #479 of 600 models, in the 20th percentile. The leader is GPT-5.2 Pro at 81.7.

Is Phi-4 7B good at SWE-bench Verified?

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 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 7B cost?

Phi-4 7B costs $0.91 per million input tokens and $3.55 per million output tokens.

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