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DeepSeek-V3.1 vs Kimi K2.5
Comprehensive side-by-side LLM comparison
Kimi K2.5 offers 128.2K more tokens in context window than DeepSeek-V3.1. DeepSeek-V3.1 is $6.13 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 K2.5, 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.
4 months newer
DeepSeek-V3.1
DeepSeek
2025-08-21
Kimi K2.5
Moonshot AI
2026-01
Pricing Comparison
Cost per million tokens (USD)
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DeepSeek-V3.1
Input:$0.27
Output:$1.10($6.13 cheaper)
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Kimi K2.5
Input:$1.50
Output:$6.00
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 K2.5
1 providers
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DeepSeek-V3.1
Avg Score:0.0%
Providers:1
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Kimi K2.5
Avg Score:0.0%
Providers:1