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DeepSeek-V3.1 vs Kimi K2 Thinking
Comprehensive side-by-side LLM comparison
Kimi K2 Thinking offers 128.2K more tokens in context window than DeepSeek-V3.1. DeepSeek-V3.1 is $3.63 cheaper per million tokens. Both models have their strengths depending on your specific coding needs.
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DeepSeek
DeepSeek-V3.1, released by DeepSeek in August 2025, is a hybrid large language model with 671 billion total parameters (37 billion active) that unifies the capabilities of DeepSeek-V3 and DeepSeek-R1 in a single model. It features a 128K token context window and supports both direct generation and extended reasoning modes selectable via the chat template. DeepSeek-V3.1 targets general-purpose tasks, coding, and complex reasoning under an open MIT license.
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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.
2 months newer
DeepSeek-V3.1
DeepSeek
2025-08-21
Kimi K2 Thinking
Moonshot AI
2025-11-06
Pricing Comparison
Cost per million tokens (USD)
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DeepSeek-V3.1
Input:$0.27
Output:$1.10($3.63 cheaper)
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Kimi K2 Thinking
Input:$1.00
Output:$4.00
Performance Metrics
Context window and performance specifications
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek-V3.1
1 providers
DeepSeek
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Kimi K2 Thinking
1 providers
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DeepSeek-V3.1
Avg Score:0.0%
Providers:1
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Kimi K2 Thinking
Avg Score:0.0%
Providers:1