Kimi K2.5 vs QwQ-32B Comparison
Performance Benchmarks
Comparative analysis across standard metrics
Kimi K2.5 outperforms in 1 benchmarks (GPQA), while QwQ-32B is better at 0 benchmarks.
Kimi K2.5 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
Cost data unavailable.
Model Size
Parameter count comparison
Kimi K2.5 has 967.5B more parameters than QwQ-32B, making it 2976.9% larger.
Context Window
Maximum input and output token capacity
Only Kimi K2.5 specifies input context (262,100 tokens). Only Kimi K2.5 specifies output context (262,100 tokens).
Input Capabilities
Supported data types and modalities
Kimi K2.5 supports multimodal inputs, whereas QwQ-32B does not.
Kimi K2.5 can handle both text and other forms of data like images, making it suitable for multimodal applications.
Kimi K2.5
QwQ-32B
License
Usage and distribution terms
Kimi K2.5 is licensed under MIT, while QwQ-32B uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Kimi K2.5 was released on 2026-01-27, while QwQ-32B was released on 2025-03-05.
Kimi K2.5 is 11 months newer than QwQ-32B.
Jan 27, 2026
1 months ago
10mo newerMar 5, 2025
1.0 years ago
Knowledge Cutoff
When training data ends
QwQ-32B has a documented knowledge cutoff of 2024-11-28, while Kimi K2.5's cutoff date is not specified.
We can confirm QwQ-32B's training data extends to 2024-11-28, but cannot make a direct comparison without Kimi K2.5's cutoff date.
—
Nov 2024
Outputs Comparison
Key Takeaways
Kimi K2.5
View detailsMoonshot AI
QwQ-32B
View detailsAlibaba Cloud / Qwen Team