Kimi K3.1 Pro Review: Moonshot AI 1M Context Window and API Details

Kimi K3.1 Pro reached public availability on October 23, 2026, as Moonshot AI's first release in the K3.1 series. The model delivers a 1,048,576-token context window and MoE architecture with 104B active parameters out of 2.8T total. It targets long-horizon coding, 3D modeling, financial analysis, and document tasks through always-on reasoning with selectable effort levels.

Kimi K3.1 Pro Capabilities and Technical Specifications

The architecture activates roughly 16 of 896 experts per token and accepts multimodal inputs including text, images, and video while producing text output. Moonshot reports substantial gains from scaled reinforcement learning across hundreds of domains compared with the July 2026 K3 base model. Independent testing on Artificial Analysis placed the model at an Intelligence Index of 55, fourth among 215 evaluated models, with particular strength in agentic workflows.

Benchmarks include 65.7 percent on Terminal-Bench 4.0, 51.7 percent on SWE-Marathon, and 92.7 percent on BenchCAD. Science tasks remain weaker at 38.1 percent on Terminal-Bench Science 0.1. A highspeed variant claims two to three times faster inference, though measured gains sit between 1.6 and 1.75 times. The model supports full-project coding in Unity, Unreal, and Godot plus parametric CAD and Blender scripting.

Reasoning effort defaults to maximum and can be lowered for speed. Cached input tokens cost less than standard input on the API. Open weights are scheduled for release on November 4, 2026, after removal of certain cyber-related training data.

API Pricing, Access, and Performance Trade-offs

Official endpoints follow OpenAI compatibility with model identifiers kimi-k3.1-pro and kimi-k3.1-pro-highspeed. Pricing stands at $2 per million input tokens and $10 per million output tokens; the highspeed version doubles those rates to $4 and $20. Cached input drops to $0.20 per million tokens. Access requires a minimum account top-up on the Kimi.ai platform or through aggregators such as OpenRouter.

Integration covers Kimi Work, Kimi Code, and mobile applications in addition to direct API calls. Registration uses standard email or OAuth flows with no additional hardware requirements beyond an internet connection. Documentation provides quick-start examples for both synchronous and streaming requests.

Security measures include targeted removal of cyber-related data for the planned open-weight release, reducing internal exploit benchmark scores from 90.5 percent to 81.0 percent. No public incidents involving data leakage have been reported since launch. The model carries no regulatory license at this stage.

Compared with Claude Opus 5.5 and GPT-6 Astra, Kimi K3.1 Pro offers a significantly larger context window at lower per-token cost. Its coding and CAD benchmarks sit close to the proprietary leader while trailing on science tasks. The open-weight timeline provides a potential cost advantage for self-hosted deployments once released.

Current limitations include the absence of released weights, narrower science performance, and the requirement for a minimum top-up before API use. Early user reports on forums note occasional latency spikes during peak hours and request clearer documentation for long-context caching. No widespread complaints about billing errors or account restrictions have surfaced in public channels.