Model Comparison
Kimi-k1.5 vs Qwen2.5-Coder 32B Instruct
Kimi-k1.5 significantly outperforms across most benchmarks.
Performance Benchmarks
Comparative analysis across standard metrics
Kimi-k1.5 outperforms in 1 benchmarks (MMLU), while Qwen2.5-Coder 32B Instruct is better at 0 benchmarks.
Kimi-k1.5 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
Cost data unavailable.
Context Window
Maximum input and output token capacity
Only Qwen2.5-Coder 32B Instruct specifies input context (128,000 tokens). Only Qwen2.5-Coder 32B Instruct specifies output context (128,000 tokens).
Input Capabilities
Supported data types and modalities
Kimi-k1.5 supports multimodal inputs, whereas Qwen2.5-Coder 32B Instruct does not.
Kimi-k1.5 can handle both text and other forms of data like images, making it suitable for multimodal applications.
Kimi-k1.5
Qwen2.5-Coder 32B Instruct
License
Usage and distribution terms
Kimi-k1.5 is licensed under a proprietary license, while Qwen2.5-Coder 32B Instruct uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Apache 2.0
Open weights
Release Timeline
When each model was launched
Kimi-k1.5 was released on 2025-01-20, while Qwen2.5-Coder 32B Instruct was released on 2024-09-19.
Kimi-k1.5 is 4 months newer than Qwen2.5-Coder 32B Instruct.
Jan 20, 2025
1.2 years ago
4mo newerSep 19, 2024
1.6 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Outputs Comparison
Key Takeaways
Kimi-k1.5
View detailsMoonshot AI
Qwen2.5-Coder 32B Instruct
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
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FAQ
Common questions about Kimi-k1.5 vs Qwen2.5-Coder 32B Instruct