Kimi K3.1 Pro Unveiled: A 2.8 Trillion Parameter Open-Weight Agent and Coding Model

The gap between open-weight large language models and closed-source commercial frontier models is narrowing a little more every day. Moonshot AI, one of the strongest players in this race, has officially announced Kimi K3.1 Pro, its new flagship model developed by thoroughly overhauling the previous-generation Kimi K3 architecture with extensive post-training optimizations. Focused on agentic workflows that demand high accuracy, such as multimodal reasoning, long-running autonomous software engineering, complex financial research and parametric 3D/CAD content generation, Kimi K3.1 Pro stands out for both its performance metrics and its reduced API costs.

According to the technical data shared by Moonshot AI and the first analyses by independent evaluators, Kimi K3.1 Pro goes beyond being a classic chatbot that only produces text answers; it is positioned as a production engine that can use tools sequentially in real development environments, verify its own output and work through data sets of millions of lines without getting lost.

A 2.8 Trillion Parameter MoE Architecture and a 1 Million Token Context Window

At the heart of Kimi K3.1 Pro is a massive-scale Sparse Mixture-of-Experts (MoE) architecture. The model holds about 2.8 trillion parameters in total, but activates only 104 billion active parameters for each token it processes. This architectural choice gives the model the deep knowledge and complex reasoning capacity of trillion-parameter systems while keeping inference costs and response latency within reasonable limits.

The model's key architectural capabilities can be grouped under these headings:

• 1 Million Token Native Context Window: With a context window of exactly 1,048,576 tokens, huge code repositories, financial statements hundreds of pages long, legal contracts and long system logs can be analyzed seamlessly in a single prompt.
• Native Multimodal Perception: Besides text input, it can directly process visual data, UI screenshots, technical diagrams and, in certain workflows, video streams.
• Reduced Hallucination Rate: Thanks to targeted post-training alignment work compared with the K3 series, the hallucination rate dropped noticeably, especially in factual claims and in interpreting data tables.
• Kimi K3.1 Pro Highspeed Variant: Alongside the standard flagship model, a dedicated Highspeed version that boosts output speed 2 to 3 times for interactive coding and real-time agent scenarios was released at the same time.

Frontier Performance in Coding, Terminal Tasks and 3D Modeling

While developing Kimi K3.1 Pro, Moonshot AI focused in particular on raising the success rate on "long-horizon" tasks. When an AI agent has to run terminal commands over dozens of steps, read error messages and fix code, and talk to external APIs, many models lose context. Kimi K3.1 Pro, however, places itself among the industry's top tier in this area:

• Terminal-Bench 4.0: Reaching a score of 65.7% on this demanding benchmark of realistic, resource-constrained terminal and software engineering tasks, Kimi K3.1 Pro leaves strong rivals such as GPT-6 Astra (58.2%) behind and sits right on the heels of closed-source leader Claude Opus 5.5 (66.4%).
• Kimi Code Bench 3.0 (Long-Horizon Coding): In multi-step tool use and large-scale project development tests, it makes a notable leap, raising the previous K3 model's 55.95% score to 61.2%.
• Parametric 3D and CAD Design: One of the model's most striking new features is how it interacts with 3D modeling environments. Kimi K3.1 Pro can generate parametric CAD scripts from written commands and fix geometry errors on its own by inspecting the rendered output of the 3D scenes it creates.
• Financial and Enterprise Analysis: It can produce end-to-end autonomous reports in multi-step data scraping, table merging and quantitative financial modeling workflows.

33% Cheaper API Pricing and the Open-Weight Timeline

Besides the performance gains, Moonshot AI also announced an aggressive price cut that delighted the developer ecosystem. Kimi K3.1 Pro's standard API usage costs are about 33% cheaper than the previous generation:

• Standard Input Cost: 2.00 dollars per 1 million tokens
• Cached Input Cost: 0.20 dollars per 1 million tokens
• Output Cost: 10.00 dollars per 1 million tokens
• Highspeed Variant Pricing: For the speed-focused version, pricing is set at 4.00 dollars per 1 million input tokens, 0.20 dollars for cache hits and 20.00 dollars for output.

The model is already available through the Kimi.ai web platform, Kimi Work, Kimi Code and the developer API, but its most exciting aspect is the promise made to the open-source community. Moonshot AI announced that it will publicly release Kimi K3.1 Pro's full model weights (open weights) by November 4, 2026. This step looks set to establish a new global standard for organizations and researchers who want to host a frontier-class coding and agent model on their own server infrastructure.