Model Comparison

Comprehensive side-by-side analysis of model capabilities and performance

Microsoft

Phi 4 Reasoning

Microsoft

Phi 4 Reasoning is a language model developed by Microsoft. It achieves strong performance with an average score of 75.1% across 11 benchmarks. It excels particularly in FlenQA (97.7%), HumanEval+ (92.9%), IFEval (83.4%). The model shows particular specialization in code tasks with an average performance of 76.7%. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Microsoft's latest advancement in AI technology.

Alibaba

QwQ-32B-Preview

Alibaba

QwQ-32B-Preview is a language model developed by Alibaba. It achieves strong performance with an average score of 64.0% across 4 benchmarks. It excels particularly in MATH-500 (90.6%), GPQA (65.2%), AIME 2024 (50.0%). The model is available through 4 API providers. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Alibaba's latest advancement in AI technology.

Alibaba

QwQ-32B-Preview

Alibaba

2024-11-28

Microsoft

Phi 4 Reasoning

Microsoft

2025-04-30

5 months newer

Performance Metrics

Context window and performance specifications

Microsoft

Phi 4 Reasoning

Max Context:-
Parameters:14.0B
Alibaba

QwQ-32B-Preview

Larger context
Max Context:65.5K
Parameters:32.5B

Average performance across 3 common benchmarks

Microsoft

Phi 4 Reasoning

+9.9%
Average Score:65.0%
Alibaba

QwQ-32B-Preview

Average Score:55.1%

Performance comparison across key benchmark categories

Microsoft

Phi 4 Reasoning

math
76.6%
code
+26.7%
76.7%
general
+16.7%
74.3%
Alibaba

QwQ-32B-Preview

math
+14.0%
90.6%
code
50.0%
general
57.6%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

QwQ-32B-Preview

2024-11-28

Phi 4 Reasoning

2025-03-01

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Microsoft

Phi 4 Reasoning

0 providers
Alibaba

QwQ-32B-Preview

4 providers

Together

Throughput: 62.14 tok/s
Latency: 0.74ms

Hyperbolic

Throughput: 31.9 tok/s
Latency: 1.05ms

DeepInfra

Throughput: 76.04 tok/s
Latency: 0.44ms

Fireworks

Throughput: 99.15 tok/s
Latency: 0.53ms
Microsoft

Phi 4 Reasoning

+9.9%
Avg Score:65.0%
Providers:0
Alibaba

QwQ-32B-Preview

Avg Score:55.1%
Providers:4