DeepSeek-V2.5 vs Kimi-k1.5
Kimi-k1.5 leads the LLM Stats Score 17.2 to 8.1.
DeepSeek · Moonshot AI · Updated for 2026
Which is better?
Kimi-k1.5 leads the overall LLM Stats Score 17.2 to 8.1, ranking #226 overall.
In the 1 individual benchmarks reported for both models, Kimi-k1.5 wins 1; this is a narrower head-to-head signal than the composite indexes.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek-V2.5
- you need open weights you can self-host or fine-tune
Choose Kimi-k1.5
- overall performance matters — it scores 17.2 and ranks #226 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- you want the most recent training data — it shipped Jan 2025
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
15 reported for DeepSeek-V2.5 · 9 for Kimi-k1.5
DeepSeek-V2.5 outperforms in 0 benchmarks, while Kimi-k1.5 is better at 1 benchmark (MMLU).
Kimi-k1.5 significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Context Window
Maximum input and output token capacity
Only DeepSeek-V2.5 specifies input context (8,192 tokens). Only DeepSeek-V2.5 specifies output context (8,192 tokens).
Input capabilities
Documented input modalities across available providers
Kimi-k1.5 supports multimodal inputs, whereas DeepSeek-V2.5 does not.
Kimi-k1.5 can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V2.5
Kimi-k1.5
License
Usage and distribution terms
DeepSeek-V2.5 is licensed under deepseek, while Kimi-k1.5 uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
deepseek
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
DeepSeek-V2.5 was released on 2024-05-08, while Kimi-k1.5 was released on 2025-01-20.
Kimi-k1.5 is 9 months newer than DeepSeek-V2.5.
May 8, 2024
2.4 years ago
Jan 20, 2025
1.7 years ago
8mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V2.5 and Kimi-k1.5 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V2.5 vs Kimi-k1.5.