Kimi K3.1 Pro
- Provider
- Moonshot AI
- Modality
- MULTIMODAL
- Parameters
- —
- Context window
- 1,000,000 tokens
- Weights
- Open
- Released
- 23 Oct 2026
Kimi K3.1 Pro (23 October 2026) is Moonshot AI's flagship — a "3T-class" model with a 1M-token context, built for coding, 3D modelling and financial research. Moonshot reports 65.7% on Terminal-Bench 4.0, close to Claude Opus 5.5's 66.4%. It runs in thinking mode only, and its open weights are due by 4 November 2026.
Best for
- Agentic coding and long-horizon software tasks
- Research and analysis over very long documents (1M context)
- Teams that want near-frontier quality with a self-hosting option later
- Kimi Code users
How it compares — and the India angle
- On Moonshot's own Terminal-Bench 4.0 table it is 0.7 points behind Claude Opus 5.5 and 7.5 ahead of GPT-6 Astra. Vals.ai independently ranks it 8th of 27 models.
- Thinking cannot be switched off — requests without it are rejected — so reasoning tokens are part of every bill.
- Moonshot removed cyber-security data from training for the open release; its internal cyber benchmark fell from 90.5% to 81.0%.
- Until 4 November it is API-only. For a fully permissive licence today, DeepSeek V4.1 Flash is MIT.
Benchmarks
Representative public scores (approximate, higher is better) for relative comparison. Check the provider for the latest official results.
How to access
API model IDs kimi-k3.1-pro and kimi-k3.1-pro-highspeed (2-3x faster). Moonshot's blog does not list prices; third-party listings give about $2 / 1M input and $10 / 1M output, Highspeed about double. Open weights due by 4 Nov 2026; licence not yet stated.
Access Kimi K3.1 ProFrequently asked questions
What is Kimi K3.1 Pro?
Kimi K3.1 Pro is a multimodal AI model developed by Moonshot AI.
Who made Kimi K3.1 Pro?
Kimi K3.1 Pro was created by Moonshot AI.
Is Kimi K3.1 Pro open source?
Yes, Kimi K3.1 Pro has open weights and can be downloaded and self-hosted.
What is Kimi K3.1 Pro's context window?
Kimi K3.1 Pro supports a context window of 1,000,000 tokens.