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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-Next-80B-A3B-Instruct

Alibaba Cloud / Qwen Team

Qwen3-Next-80B-A3B-Instruct is a language model developed by Alibaba Cloud / Qwen Team. It achieves strong performance with an average score of 67.0% across 24 benchmarks. It excels particularly in MMLU-Redux (90.9%), MultiPL-E (87.8%), IFEval (87.6%). It supports a 131K 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.

Alibaba Cloud / Qwen Team

Qwen3-Next-80B-A3B-Instruct

Alibaba Cloud / Qwen Team

2025-01-10

Microsoft

Phi 4 Mini

Microsoft

2025-02-01

22 days newer

Performance Metrics

Context window and performance specifications

Microsoft

Phi 4 Mini

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

Qwen3-Next-80B-A3B-Instruct

Larger context
Max Context:131.1K
Parameters:80.0B

Average performance across 2 common benchmarks

Microsoft

Phi 4 Mini

Average Score:39.0%
Alibaba Cloud / Qwen Team

Qwen3-Next-80B-A3B-Instruct

+37.8%
Average Score:76.8%

Performance comparison across key benchmark categories

Microsoft

Phi 4 Mini

factuality
66.4%
general
60.8%
reasoning
+14.5%
73.3%
math
+26.3%
72.2%
Alibaba Cloud / Qwen Team

Qwen3-Next-80B-A3B-Instruct

factuality
+24.5%
90.9%
general
+15.0%
75.8%
reasoning
58.8%
math
45.9%
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-Next-80B-A3B-Instruct

1 providers

Novita

Microsoft

Phi 4 Mini

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

Qwen3-Next-80B-A3B-Instruct

+37.8%
Avg Score:76.8%
Providers:1