Model Comparison
DeepSeek-V3.2-Exp vs Kimi K3Which is better in 2026?
Kimi K3 significantly outperforms across most benchmarks. DeepSeek-V3.2-Exp is 19.7x cheaper per token.
Verdict: DeepSeek-V3.2-Exp vs Kimi K3 — which is better?
DeepSeek-V3.2-Exp (by DeepSeek) and Kimi K3 (by Moonshot AI) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
DeepSeek-V3.2-Exp outperforms in 0 benchmarks, while Kimi K3 is better at 3 benchmarks (BrowseComp, GPQA, Humanity's Last Exam). Kimi K3 significantly outperforms across most benchmarks.
On price, DeepSeek-V3.2-Exp is roughly 19.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Kimi K3 also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Choose DeepSeek-V3.2-Exp if…
- cost matters — it's about 19.7x cheaper per token
Choose Kimi K3 if…
- you want the strongest raw capability — it leads on 3 of 3 shared benchmarks
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Jul 2026
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V3.2-Exp outperforms in 0 benchmarks, while Kimi K3 is better at 3 benchmarks (BrowseComp, GPQA, Humanity's Last Exam).
Kimi K3 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V3.2-Exp ($0.27/1M tokens) is 11.1x cheaper than Kimi K3 ($3.00/1M tokens).
For output processing, DeepSeek-V3.2-Exp ($0.41/1M tokens) is 36.6x cheaper than Kimi K3 ($15.00/1M tokens).
In conclusion, Kimi K3 is more expensive than DeepSeek-V3.2-Exp.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Kimi K3 has 2115.0B more parameters than DeepSeek-V3.2-Exp, making it 308.8% larger.
Context Window
Maximum input and output token capacity
Kimi K3 accepts 1,048,576 input tokens compared to DeepSeek-V3.2-Exp's 163,840 tokens. Kimi K3 can generate longer responses up to 1,048,576 tokens, while DeepSeek-V3.2-Exp is limited to 65,536 tokens.
Input Capabilities
Supported data types and modalities
Kimi K3 supports multimodal inputs, whereas DeepSeek-V3.2-Exp does not.
Kimi K3 can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V3.2-Exp
Kimi K3
License
Usage and distribution terms
DeepSeek-V3.2-Exp is licensed under MIT, while Kimi K3 uses Kimi K3 License.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Kimi K3 License
Open weights
Release Timeline
When each model was launched
DeepSeek-V3.2-Exp was released on 2025-09-29, while Kimi K3 was released on 2026-07-16.
Kimi K3 is 10 months newer than DeepSeek-V3.2-Exp.
Sep 29, 2025
10 months ago
Jul 16, 2026
3 weeks ago
9mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-V3.2-Exp is available from Novita. Kimi K3 is available from Fireworks, Moonshot AI, Novita, Together.
DeepSeek-V3.2-Exp
Kimi K3
Outputs Comparison
Key Takeaways
DeepSeek-V3.2-Exp
View detailsDeepSeek
Kimi K3
View detailsMoonshot AI
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against DeepSeek-V3.2-Exp and Kimi K3 side-by-side, then vote on the output you prefer.
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FAQ
Common questions about DeepSeek-V3.2-Exp vs Kimi K3.