Kimi K2 Base vs Qwen2.5-Coder 32B Instruct Comparison
Comparing Kimi K2 Base and Qwen2.5-Coder 32B Instruct across benchmarks, pricing, and capabilities.
Performance Benchmarks
Comparative analysis across standard metrics
Kimi K2 Base outperforms in 4 benchmarks (GSM8k, MATH, MMLU, MMLU-Pro), while Qwen2.5-Coder 32B Instruct is better at 0 benchmarks.
Kimi K2 Base 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 Base has 968.0B more parameters than Qwen2.5-Coder 32B Instruct, making it 3025.0% larger.
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).
License
Usage and distribution terms
Kimi K2 Base is licensed under MIT, 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.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Kimi K2 Base was released on 2025-07-11, while Qwen2.5-Coder 32B Instruct was released on 2024-09-19.
Kimi K2 Base is 10 months newer than Qwen2.5-Coder 32B Instruct.
Jul 11, 2025
8 months ago
9mo newerSep 19, 2024
1.5 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 K2 Base
View detailsMoonshot AI
Qwen2.5-Coder 32B Instruct
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
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