Reasoning · Microsoft

Phi-4 7B on GPQA Diamond: score, rank and what it means

Phi-4 7B scores 52.7 on GPQA Diamond, placing it #492 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
52.7
0–100 scale
Rank
#492
of 600
Percentile
18th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
34.3
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with Phi-4 7B highlighted. Longer bars mean higher scores.

GPT-5.2 Reasoning 87.0
GPT-5.1 Max 86.4
Claude Opus 4.5 Pro 86.0
GPT-5.1 Reasoning 85.6
Claude Sonnet 4.5 Reasoning 85.2
GPT-5.2 84.9
o4 Turbo 84.8
Claude Opus 4.5 Max 84.6
Grok 4 Turbo 84.5
Claude Sonnet 4.5 Max 84.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
2 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
3 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
4 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
5 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
6 GPT-5.2 OpenAI 2000000 $19.71 88.0
7 o4 Turbo OpenAI 2000000 $19.34 86.6
8 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
9 Grok 4 Turbo xAI 1000000 $19.21 86.7
10 Claude Sonnet 4.5 Max Anthropic 1000000 $19.90 87.2

What this score means

On GPQA Diamond, Phi-4 7B sits at #492 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 34.3 points. The median model in this index scores 68.8, which puts Phi-4 7B below the midpoint.

Microsoft models average 58.6 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 49.3. Phi-4 7B is 3.4 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 52.7 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 GPQA Diamond. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Codestral 8B Mistral AI 4096 $1.18 59.0
Phi-4 8B Microsoft 32768 $0.96 54.9
Magistral 8B Mistral AI 4096 $1.33 60.0
Llama 3 DeepInfra 8B DeepInfra 8192 $1.05 57.4
Phi-4 7B Microsoft 8192 $0.91 56.8
Firesearch Nano Fireworks AI 8192 $2.49 55.6
Firefunction Nano Fireworks AI 16384 $3.07 58.1

Other benchmarks for Phi-4 7B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 62.4 498 17th
SWE-bench Verified 44.0 479 20th
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 GPQA Diamond?

Phi-4 7B scores 52.7 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does Phi-4 7B rank on GPQA Diamond?

It ranks #492 of 600 models, in the 18th percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is Phi-4 7B good at GPQA Diamond?

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 GPQA Diamond score calculated?

GPQA Diamond is a reasoning 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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