DeepSeek-V3 vs Kimi-k1.5
DeepSeek-V3 and Kimi-k1.5 are closely matched at 15.7 and 17.2 on the LLM Stats Score.
DeepSeek · Moonshot AI · Updated for 2026
Which is better?
DeepSeek-V3 and Kimi-k1.5 are closely matched on the overall LLM Stats Score at 15.7 and 17.2.
In the 6 individual benchmarks reported for both models, Kimi-k1.5 wins 5; 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-V3
- you need open weights you can self-host or fine-tune
Choose Kimi-k1.5
- you value its reported benchmark strengths — it wins 5 of 6 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
20 reported for DeepSeek-V3 · 9 for Kimi-k1.5
DeepSeek-V3 outperforms in 1 benchmarks (MMLU), while Kimi-k1.5 is better at 5 benchmarks (AIME 2024, C-Eval, CLUEWSC, IFEval, MATH-500).
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-V3 specifies input context (131,072 tokens). Only DeepSeek-V3 specifies output context (131,072 tokens).
Input capabilities
Documented input modalities across available providers
Kimi-k1.5 supports multimodal inputs, whereas DeepSeek-V3 does not.
Kimi-k1.5 can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V3
Kimi-k1.5
License
Usage and distribution terms
DeepSeek-V3 is licensed under MIT + Model License (Commercial use allowed), while Kimi-k1.5 uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT + Model License (Commercial use allowed)
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
DeepSeek-V3 was released on 2024-12-25, while Kimi-k1.5 was released on 2025-01-20.
Kimi-k1.5 is 1 month newer than DeepSeek-V3.
Dec 25, 2024
1.8 years ago
Jan 20, 2025
1.7 years ago
3w 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-V3 and Kimi-k1.5 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V3 vs Kimi-k1.5.