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DeepSeek-V3.2 Thinking vs Kimi K2.5
Comprehensive side-by-side LLM comparison
Kimi K2.5 leads with 3.7% higher average benchmark score. Kimi K2.5 offers 128.2K more tokens in context window than DeepSeek-V3.2 Thinking. DeepSeek-V3.2 Thinking is $4.76 cheaper per million tokens. Both models have their strengths depending on your specific coding needs.
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DeepSeek
DeepSeek-V3.2-Exp (DeepSeek-V3.2 Thinking), released by DeepSeek in September 2025, is the experimental preview release of the DeepSeek-V3.2 model featuring 685 billion total parameters and integrated thinking capabilities. It introduced the architecture and training approaches that became the foundation of the final V3.2 release, including thinking in tool-use and hybrid reasoning modes.
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Moonshot AI
Kimi K2.5, released by Moonshot AI in January 2026, is an updated Mixture-of-Experts large language model with 1 trillion total parameters and 32 billion active parameters. It builds on Kimi K2 with improved coding performance across multiple languages and an expanded context window. Kimi K2.5 targets agentic development workflows, polyglot code generation, and open-source deployments requiring large-scale MoE reasoning.
3 months newer
DeepSeek-V3.2 Thinking
DeepSeek
2025-09-29
Kimi K2.5
Moonshot AI
2026-01
Pricing Comparison
Cost per million tokens (USD)
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DeepSeek-V3.2 Thinking
Input:$0.55
Output:$2.19($4.76 cheaper)
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Kimi K2.5
Input:$1.50
Output:$6.00
Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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DeepSeek-V3.2 Thinking
Average Score:73.1%
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Kimi K2.5
Average Score:76.8%(+3.7%)
Performance comparison across key benchmark categories
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DeepSeek-V3.2 Thinking
Coding73.1%
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Kimi K2.5
Coding76.8%(+3.7%)
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek-V3.2 Thinking
1 providers
DeepSeek
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Kimi K2.5
1 providers
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DeepSeek-V3.2 Thinking
Avg Score:73.1%
Providers:1
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Kimi K2.5
Avg Score:76.8%(+3.7%)
Providers:1