Kimi vs DeepSeek (2026): Kimi K3.1 Pro or DeepSeek V4.1 Flash?
Two of the strongest open AI models from China, compared on price, context, open weights, access and privacy, with a clear pick for coding, research and budgets.
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Kimi (from Moonshot AI) and DeepSeek both shipped big updates in October 2026, and both are serious alternatives to the US labs at a fraction of the price. Here’s how they compare.
Quick answer: pick Kimi K3.1 Pro for the strongest coding and agent work, and DeepSeek V4.1 Flash when cost is what matters most.
Kimi vs DeepSeek at a glance
| Kimi K3.1 Pro | DeepSeek V4.1 Flash (1017) | |
|---|---|---|
| Maker | Moonshot AI | DeepSeek |
| Released | Oct 23, 2026 | Oct 17, 2026 (first version Sep 10) |
| API price (in / out, per 1M tokens) | $2 / $10 (cached $0.20) | $0.30 / $1.20 peak, half that off-peak |
| Context window | 1M tokens | 1M tokens (up to 384K output) |
| Open weights | Promised by Nov 4, 2026 | Yes, on Hugging Face and ModelScope |
| Where to use it | Kimi.com, Kimi apps, Kimi Code, API | DeepSeek app and web chat (free), API |
| Notable | Thinking mode always on; Highspeed version 2 to 3x faster | Shorter, faster answers in the 1017 update |
From each company’s own pages, checked October 28, 2026.
Kimi K3.1 Pro: the stronger coder (by its own numbers)
Kimi K3.1 Pro is the first model in Moonshot’s K3.1 series and, by Moonshot’s description, its most capable open-weight model yet. Moonshot reports 65.7% on Terminal-Bench 4.0, a test of coding agents, close to Claude Opus 5.5. That’s the company’s own figure, not an independent test.
At $2 / $10 it costs a fraction of the US flagships, and there’s a Highspeed version that answers two to three times faster. One quirk: thinking mode is always on.
DeepSeek V4.1 Flash: the budget champion
DeepSeek V4.1 Flash launched on September 10, 2026, and the October 17 update (Flash-1017) made it faster, with shorter answers and better benchmark scores by DeepSeek’s account. Its big advantage is price: $0.30 / $1.20 at peak times, and half that off-peak. Cached input costs a fraction of a cent.
The weights are already public, and the DeepSeek app and web chat are free.
Privacy
Both are Chinese companies. Before sending anything sensitive, read each privacy policy and check where data is processed. DeepSeek’s terms say the service is intended for adults, with guardian consent needed under 18. The safest route for private data is to run the open weights on your own hardware, possible for DeepSeek now and for Kimi once the weights are out.
Which should you choose?
- Choose Kimi K3.1 Pro for coding agents and long research tasks where quality comes first.
- Choose DeepSeek V4.1 Flash for high-volume work, budget projects, or when you want open weights today.
Want more models you can run yourself? See the best open-weight AI models, or browse every release in our new models tracker.
Tools in this post

Kimi
by Moonshot AI
Assistant for long documents, research and coding, powered by the open-weight Kimi K3.1 models.

DeepSeek
by DeepSeek
Free chat assistant from Chinese lab DeepSeek, strong at reasoning and coding.
Free app and web chat; paid API for developers
Privacy & risks
- Trains on your data
- Yes
- Minimum age
- Intended for adults; under 18 needs guardian consent
- Its privacy policy says user data is used to train its models.
- Data is processed by a Chinese company. Check your employer's or school's rules before using it with work or personal data.
Questions people ask
Is Kimi better than DeepSeek?
For coding agents, Moonshot reports strong results for Kimi K3.1 Pro, including 65.7% on Terminal-Bench 4.0. DeepSeek V4.1 Flash is much cheaper. Which is better depends on whether quality or cost matters more for your task.
Are Kimi and DeepSeek open source?
DeepSeek V4.1 Flash-1017's weights are on Hugging Face and ModelScope. Moonshot says Kimi K3.1 Pro's full weights will be released by November 4, 2026.
Is it safe to use Kimi or DeepSeek?
For anything sensitive, check each provider's privacy policy and where your data is processed. Running the open weights on your own hardware keeps your data in-house.


