DeepSeek-V4-Pro-0813 vs Kimi K3
DeepSeek-V4-Pro-0813 and Kimi K3 are closely matched at 52.1 and 53.1 on the LLM Stats Score. DeepSeek-V4-Pro-0813 is 10.5x cheaper per token.
DeepSeek · Moonshot AI · Updated for 2026
Which is better?
DeepSeek-V4-Pro-0813 and Kimi K3 are closely matched on the overall LLM Stats Score at 52.1 and 53.1.
In the 5 individual benchmarks reported for both models, DeepSeek-V4-Pro-0813 wins 3; this is a narrower head-to-head signal than the composite indexes.
On price, DeepSeek-V4-Pro-0813 is roughly 10.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek-V4-Pro-0813
- you value its reported benchmark strengths — it wins 3 of 5 exact shared results
- cost matters — it's about 10.5x cheaper per token
- you want the most recent training data — it shipped Aug 2026
Choose Kimi K3
- you want predictable pricing at $2.85/M input and $14.25/M output
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
12 reported for DeepSeek-V4-Pro-0813 · 31 for Kimi K3
DeepSeek-V4-Pro-0813 outperforms in 3 benchmarks (AutomationBench, Humanity's Last Exam, Toolathlon), while Kimi K3 is better at 2 benchmarks (DeepSWE, Terminal-Bench 2.1).
DeepSeek-V4-Pro-0813 has a slight edge in benchmark performance.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Pro-0813 ($0.43/1M tokens) is 6.6x cheaper than Kimi K3 ($2.85/1M tokens).
For output processing, DeepSeek-V4-Pro-0813 ($0.87/1M tokens) is 16.4x cheaper than Kimi K3 ($14.25/1M tokens).
In conclusion, Kimi K3 is more expensive than DeepSeek-V4-Pro-0813.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Kimi K3 has 1200.0B more parameters than DeepSeek-V4-Pro-0813, making it 75.0% larger.
Context Window
Maximum input and output token capacity
Both models have the same input context window of 1,048,576 tokens. Kimi K3 can generate longer responses up to 1,048,576 tokens, while DeepSeek-V4-Pro-0813 is limited to 393,216 tokens.
Input capabilities
Documented input modalities across available providers
Kimi K3 supports multimodal inputs, whereas DeepSeek-V4-Pro-0813 does not.
Kimi K3 can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V4-Pro-0813
Kimi K3
License
Usage and distribution terms
DeepSeek-V4-Pro-0813 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-V4-Pro-0813 was released on 2026-08-13, while Kimi K3 was released on 2026-07-16.
DeepSeek-V4-Pro-0813 is 1 month newer than Kimi K3.
Aug 13, 2026
4 weeks ago
4w newerJul 16, 2026
1 months ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-V4-Pro-0813 is available from DeepSeek, DeepInfra, Novita, Together. Kimi K3 is available from DeepInfra, Fireworks, Moonshot AI, Novita, Together.
DeepSeek-V4-Pro-0813
Kimi K3
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Pro-0813 and Kimi K3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Pro-0813 vs Kimi K3.