Model Comparison

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

Phi 4

Microsoft

Phi 4 is a language model developed by Microsoft. It achieves strong performance with an average score of 66.0% across 13 benchmarks. It excels particularly in MMLU (84.8%), HumanEval+ (82.8%), HumanEval (82.6%). The model shows particular specialization in math tasks with an average performance of 80.5%. The model is available through 1 API provider. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Microsoft's latest advancement in AI technology.

Qwen3-Next-80B-A3B-Thinking

Alibaba Cloud / Qwen Team

Qwen3-Next-80B-A3B-Thinking is a language model developed by Alibaba Cloud / Qwen Team. It achieves strong performance with an average score of 67.9% across 23 benchmarks. It excels particularly in MMLU-Redux (92.5%), IFEval (88.9%), AIME25 (87.8%). 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.

Phi 4

Microsoft

2024-12-12

Qwen3-Next-80B-A3B-Thinking

Alibaba Cloud / Qwen Team

2025-01-10

29 days newer

Pricing Comparison

Cost per million tokens (USD)

Phi 4

$1.44 cheaper

Input:$0.07

Output:$0.14

Qwen3-Next-80B-A3B-Thinking

Input:$0.15

Output:$1.50

Performance Metrics

Context window and performance specifications

Phi 4

Max Context:32.0K

Parameters:14.7B

Qwen3-Next-80B-A3B-Thinking

Larger context

Max Context:131.1K

Parameters:80.0B

Average performance across 3 common benchmarks

Phi 4

Average Score:63.2%

Qwen3-Next-80B-A3B-Thinking

+19.8%

Average Score:82.9%

Performance comparison across key benchmark categories

Phi 4

factuality

3.0%

math

+24.2%

80.5%

general

66.6%

code

+24.1%

76.1%

Qwen3-Next-80B-A3B-Thinking

factuality

+89.5%

92.5%

math

56.3%

general

+11.0%

77.6%

code

52.0%

Benchmark Scores - Detailed View

Side-by-side comparison of all benchmark scores

Knowledge Cutoff

Training data recency comparison

Phi 4

2024-06-01

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Phi 4

1 providers

DeepInfra

Throughput: 33 tok/s

Latency: 0.2ms

Qwen3-Next-80B-A3B-Thinking

1 providers

Novita

Phi 4

Avg Score:63.2%

Providers:1

Qwen3-Next-80B-A3B-Thinking

+19.8%

Avg Score:82.9%

Providers:1