Moonshot AI releases Kimi-K3.1-Pro multimodal agentic model
In short: Moonshot AI has introduced Kimi-K3.1-Pro, an open-weight, natively multimodal model with 2.8 trillion parameters. It features a 1-million-token context window, uses a Mixture-of-Experts (MoE) architecture, and is specifically optimized for agentic workflows and long-horizon tasks.
This summary was generated automatically by AI from Moonshot Kimi (Hugging Face)'s publication. It is our own text, not a copy of the original — facts, figures and quotes belong to the source, linked above and below.
What changed?
- 12.8T parameter Mixture-of-Experts (MoE) architecture
- 21,048,576 token context window
- 3Support for text and image modalities
- 4New Gated DSA (DeepSeek Sparse Attention) layers
- 5OpenAI/Anthropic-compatible API support
| Parameter | Before | Now |
|---|---|---|
| Context window | Not specified | 1,048,576 |
| Architecture | Not specified | Mixture-of-Experts (MoE) 2.8T total parameters |
| Vision Encoder | Not specified | MoonViT-V2 |
Why it matters
This model provides an alternative for high-complexity reasoning and agentic tasks requiring long-range dependencies. Its performance on coding and automation benchmarks suggests it is a robust option for building sophisticated AI agents that need to handle complex, multi-turn tool calling.
What it means for AI agents and contact centers
When testing this model for voice agents or contact center automation, evaluate its reasoning capabilities alongside its 1M context window for maintaining state over long calls. Compare latency and tool-calling reliability against your current stack, particularly when using its 'max' reasoning effort for complex intent resolution.
🧪 Worth Testing
The model's high performance in agentic benchmarks and large context capabilities warrant evaluation for complex, multi-turn AI agent scenarios.
Sources
- Moonshot Kimi (Hugging Face)OfficialPrimary sourceOriginal article →„moonshotai/Kimi-K3.1-Pro released on Hugging Face (image-text-to-text)“2 Nov 2026, 06:13Licence: Model card; license per model · our summary (content changed)
- Published by source
- 2 Nov 2026, 06:13
- Found by our system
- 4 Nov 2026, 17:36
- Summary generated
- 4 Nov 2026, 19:36
This article was written by AI from the original source. Facts, numbers and prices come from the source; missing values are marked “Not specified”. Legal notice, copyright and privacy