Comprehensive side-by-side LLM comparison
Kimi K2 Thinking leads with 6.3% higher average benchmark score. Kimi K2 Thinking offers 128.2K more tokens in context window than DeepSeek-V3.2. DeepSeek-V3.2 is $3.63 cheaper per million tokens. Overall, Kimi K2 Thinking is the stronger choice for coding tasks.
DeepSeek
DeepSeek-V3.2, released by DeepSeek on December 1, 2025, is a large language model with 685 billion total parameters featuring integrated thinking in tool-use and support for both reasoning and direct generation modes. It features a 128K token context window and introduced large-scale agent training across 1,800+ environments. DeepSeek-V3.2 targets agentic workflows, complex instruction following, and coding tasks under an open MIT license.
Moonshot AI
Kimi K2 Thinking, released by Moonshot AI on November 6, 2025, is a reasoning-focused variant of Kimi K2 with 1 trillion total parameters and 32 billion active parameters, featuring extended chain-of-thought processing for complex problem solving. It builds on K2's agentic coding strengths with additional capabilities for mathematical and scientific reasoning. Kimi K2 Thinking targets open-source deployments requiring deep, deliberate reasoning across coding and analytical domains.
25 days newer
Kimi K2 Thinking
Moonshot AI
2025-11-06

DeepSeek-V3.2
DeepSeek
2025-12-01
Cost per million tokens (USD)
DeepSeek-V3.2
Kimi K2 Thinking
Context window and performance specifications
Average performance across 1 common benchmarks
DeepSeek-V3.2
Kimi K2 Thinking
Performance comparison across key benchmark categories
DeepSeek-V3.2
Kimi K2 Thinking
Available providers and their performance metrics
DeepSeek-V3.2
DeepSeek
Kimi K2 Thinking
DeepSeek-V3.2
Kimi K2 Thinking
DeepSeek-V3.2
Kimi K2 Thinking
Moonshot AI