Kimi K3.1 Pro Explained for Business Teams

Kimi K3.1 Pro is Moonshot AI's post-trained update to Kimi K3. It has a 1-million-token context window and costs $2.00 per million input tokens and $10.00 per million output tokens. Moonshot AI has promised open weights by November 4, 2026.

At Layer3Labs, we build custom agents and enterprise integrations for business teams. For a business, the case for K3.1 Pro is the lower price and long context. The case against is slow, verbose output and a data-residency review before any API use.

What Kimi K3.1 Pro Delivers

Kimi K3.1 Pro is the first release in the K3.1 series. Moonshot AI calls it its most capable 3T-class open-weight model to date, though the weights are not out yet. Moonshot AI built it as a post-trained version of Kimi K3, investing larger post-training compute and using large-scale joint reinforcement learning across hundreds of downstream domains. The model processes up to 1,048,576 tokens of context in both text and image formats, returning text output.

Pricing on the pay-as-you-go API sits lower than the predecessor model. Moonshot AI sets standard API rates at $2.00 per million input tokens and $10.00 per million output tokens, compared to $3.00 input and $15.00 output on the older Kimi K3 pricing schedule. Cached input drops to $0.20 per million tokens under an automatic 5-minute context-caching window, representing a 90% discount on cache hits. For applications needing lower latency, Moonshot AI also launched Kimi K3.1 Pro Highspeed, which claims 2x to 3x the speed of standard K3.1 Pro at $4.00 per million input tokens and $20.00 per million output tokens.

The model weights remain unavailable today. While Moonshot AI promises full model weights by November 4, 2026, the model functions strictly as an API endpoint and hosted interface right now. The Kimi K3.1 Pro vs Kimi K3 comparison covers the upgrade question. For now you get lower API token rates and more post-training, but you must use the hosted service until the weights ship.

• 1,048,576 tokens of context for long documents and complex codebases
• Standard API pricing at $2.00 per million input tokens and $10.00 per million output tokens
• Highspeed tier at $4.00 per million input tokens and $20.00 per million output tokens
• Context caching discount down to $0.20 per million tokens with a default 5-minute TTL
• Full model weights promised by Moonshot AI by November 4, 2026

Moonshot AI Reported Capability Gains

Moonshot AI reports gains across software engineering, 3D modeling, and analytical reasoning when running Kimi K3.1 Pro at maximum reasoning effort. On Terminal-Bench 4.0, Moonshot AI reports a score of 65.7% for K3.1 Pro, placing it ahead of GPT-6 Astra at 58.2% and near Claude Opus 5.5 at 66.4%. On the vendor's internal Kimi Code Bench 3.0 Long-horizon test, K3.1 Pro scored 61.2% versus 55.95% for K3.

Software development claims extend directly into modern game engines and interactive frameworks. Moonshot AI states that K3.1 Pro generates code across Unity, Unreal Engine, and Godot while integrating live web search and 3D asset generation. The vendor reports strong proficiency with Three.js web scenes and notes that in one internal simulation test, the model completed 167 autonomous missions and 420 independent reviews to assemble a functional human walking simulator.

For non-software enterprise tasks, Moonshot AI highlights gains in document processing and numeric calculation. The model scored 64.4 on OfficeQA Pro v2, which Moonshot AI describes as state of the art. In company finance benchmarks compared to original K3, Moonshot AI reports gains of 7.2 points in Financial Modeling, 11.6 points in Financial Research, and roughly 4.2x in Business Operation tasks. On Kimi Hallu Bench Hard, an internal stress test, the vendor reports claim-level hallucination rates dropped from 23.4% on K3 down to 8.3% on K3.1 Pro. 3D Make is live on kimi.ai and the Kimi app. You can preview and edit 3D models, download them for 3D printing, or export them as video or Live Photo. Moonshot says the model can also write and run Blender and CAD scripts without MCP connectors.

• Terminal-Bench 4.0 score of 65.7% reported by Moonshot AI at maximum reasoning effort
• OfficeQA Pro v2 score of 64.4, claimed as state of the art for office workflows
• Internal finance gains of +7.2 in modeling and +11.6 in research over Kimi K3
• Hallucination rate on internal stress test reduced from 23.4% down to 8.3%
• Works across Unity, Unreal Engine, and Godot, plus Blender and CAD scripts without MCP connectors

Independent Benchmarks and Evaluation Disputes

Artificial Analysis ranks Kimi K3.1 Pro 4th of 215 on its Intelligence Index, and it also rates the model slow and very verbose. A publication headline at ModelCompare argued that Kimi K3.1 Pro puts open-source AI a month behind the best. The Kimi K3.1 Pro benchmarks guide splits independent scores from Moonshot's own.

Generation speed remains a documented weakness on the standard API tier. Artificial Analysis recorded an output speed of 57.5 tokens per second, ranking the model 141st out of 186 systems and classifying it as notably slow. Running the Intelligence Index required 150 million output tokens due to very verbose generation, compared to an 87-million-token median across other models, resulting in an estimated cost of $2.11 per evaluation task.

Community forum posts are split. One headline puts K3.1 Pro 3 points behind Claude Opus 5.5 on the Artificial Analysis index. One poster says it does not look much better than DeepSeek 4.1 Flash, another says it seems slightly worse than GPT 6.1 Sol at certain tasks, and another argues the index does not represent real-world performance. These are opinions, not measurements. Artificial Analysis labels K3.1 Pro 'Proprietary model' on its page, while Moonshot AI calls it open-weight with weights pending.

• Intelligence Index score of 55 on Artificial Analysis, ranking 4th out of 215 models
• Generation speed of 57.5 tokens per second, ranking 141st of 186 tested models
• High token verbosity, using 150M tokens to complete tests against an 87M benchmark median
• Discrepancy between vendor open-weight claims and hosted proprietary delivery status
• One community poster says it does not look much better than DeepSeek 4.1 Flash

Open Weights and Data Handling Safeguards

Data security and regional hosting require strict legal review before sending corporate records to Moonshot AI. Moonshot AI is based in China, meaning business leaders must evaluate compliance policies, client confidentiality agreements, and data residency restrictions before directing sensitive documents to its servers. Zero Data Retention is available for Kimi API customers, and Kimi Business provides member management with separation between personal and organization accounts, but leadership must review cross-border transmission rules with internal legal counsel rather than assuming compliance.

Moonshot AI implemented specific data filtering to restrict offensive cyber risks before the scheduled weight release. The vendor identified and removed cyber-related training data from both mid-training corpora and the reinforcement learning environment mix. On xdev-bench-hard, Moonshot AI's in-house software vulnerability benchmark using pass@3, a checkpoint without the cyber-data removal solved 90.5% of problems, whereas the production K3.1 Pro model reached 81.0%. Moonshot AI states that offensive cyber capabilities remain behind frontier proprietary models that have been public for at least three months.

Moonshot AI has promised the weights by November 4, 2026. Until they ship, you can only reach the model through the hosted service.

• Zero Data Retention option available for Kimi API customers
• Kimi Business provides account separation between personal and company users
• Enterprise administrators must verify data residency and cross-border transfer rules with counsel
• Moonshot reports 81.0% on its in-house xdev-bench-hard vulnerability test, versus 90.5% for a checkpoint without the cyber-data removal
• Self-hosting is not possible until Moonshot releases the weights it has promised by Nov 4, 2026

Deployment Options and Enterprise Workflows

Kimi K3.1 Pro is available in four places. Everyday users get it on kimi.ai and in Kimi Work. Kimi Work is a desktop app (version 3.1.0 or later) for Windows and Apple silicon Macs. Developers can access the model inside Kimi Code using the /model command, or connect software pipelines directly to the Kimi API chat endpoints under model identifiers kimi-k3.1-pro and kimi-k3.1-pro-highspeed.

IT administrators should note that enterprise access remains restricted initially. For Kimi Enterprise accounts, administrator controls have K3.1 Pro access turned off by default at launch, requiring manual activation before employees can query the model. API developers can adjust the reasoning_effort parameter across low, high, and max settings to balance analytical depth against token consumption and latency. File extraction and file storage APIs remain temporarily free on the platform. Meanwhile, older K2 series models will stop being available to newly registered users from October 31, 2026, with full retirement scheduled by December 2026.

Artificial Analysis rates this model slow, so test it before using it for latency-critical work. If your team needs low-latency conversational streaming, standard K3.1 Pro's 57.5 tokens per second and verbose output may cause noticeable delays. Teams with data-residency limits should review the API with counsel first. Our verdict would flip toward broader enterprise recommendation if Moonshot AI releases the weights it has promised by November 4, 2026, so teams could self-host and run extraction inside their own infrastructure, which removes the API data-transfer question. For teams ready to test long-context processing, map two pilot document extraction tasks and test prompt token caching to measure actual speed and cost.

• Web access via kimi.ai and desktop workflows on Kimi Work version 3.1.0 or later
• Developer integration in Kimi Code via /model and programmatic access on the Kimi API
• Kimi Enterprise administrative toggle is disabled by default at launch
• Adjustable reasoning_effort parameters supporting low, high, and max settings
• K2 series models phased out for new accounts from October 31, 2026