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Model Comparison

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

Microsoft

Phi 4 Mini

Microsoft

Phi 4 Mini is a language model developed by Microsoft. It achieves strong performance with an average score of 65.4% across 17 benchmarks. It excels particularly in GSM8k (88.6%), ARC-C (83.7%), BoolQ (81.2%). 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 Cloud / Qwen Team

Qwen3-235B-A22B-Thinking-2507

Alibaba Cloud / Qwen Team

Qwen3-235B-A22B-Thinking-2507 is a language model developed by Alibaba Cloud / Qwen Team. It achieves strong performance with an average score of 69.2% across 25 benchmarks. It excels particularly in MMLU-Redux (93.8%), AIME25 (92.3%), WritingBench (88.3%). It supports a 387K token context window for handling large documents. The model is available through 1 API provider. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Alibaba Cloud / Qwen Team's latest advancement in AI technology.

Microsoft

Phi 4 Mini

Microsoft

2025-02-01

Alibaba Cloud / Qwen Team

Qwen3-235B-A22B-Thinking-2507

Alibaba Cloud / Qwen Team

2025-07-25

5 months newer

Performance Metrics

Context window and performance specifications

Microsoft

Phi 4 Mini

Max Context:-
Parameters:3.8B
Alibaba Cloud / Qwen Team

Qwen3-235B-A22B-Thinking-2507

Larger context
Max Context:387.1K
Parameters:235.0B

Average performance across 2 common benchmarks

Microsoft

Phi 4 Mini

Average Score:39.0%
Alibaba Cloud / Qwen Team

Qwen3-235B-A22B-Thinking-2507

+43.8%
Average Score:82.8%

Performance comparison across key benchmark categories

Microsoft

Phi 4 Mini

factuality
66.4%
general
60.8%
reasoning
+8.4%
73.3%
math
+12.1%
72.2%
Alibaba Cloud / Qwen Team

Qwen3-235B-A22B-Thinking-2507

factuality
+27.4%
93.8%
general
+16.5%
77.4%
reasoning
64.9%
math
60.1%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Phi 4 Mini

2024-06-01

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Microsoft

Phi 4 Mini

0 providers
Alibaba Cloud / Qwen Team

Qwen3-235B-A22B-Thinking-2507

1 providers

Novita

Microsoft

Phi 4 Mini

Avg Score:39.0%
Providers:0
Alibaba Cloud / Qwen Team

Qwen3-235B-A22B-Thinking-2507

+43.8%
Avg Score:82.8%
Providers:1