Quick Answer
Kimi K3.1 Pro is Moonshot AI’s new 3T-class open-weight model, with a 1-million-token context window and reasoning enabled by default. Moonshot says the model is available now through Kimi.ai, Kimi Work, Kimi Code, and its API, while full weights are planned by November 4. Developers should treat the benchmark claims as self-reported and test the model on their own workloads.
Key Takeaways
- Kimi K3.1 Pro launched on October 24, 2026, as Moonshot AI’s first K3.1-series model.
- Kimi K3.1 Pro supports a 1-million-token context window.
- Kimi K3.1 Pro Highspeed is advertised at two to three times the standard model’s speed.
- Moonshot plans to release the full K3.1 Pro weights by November 4, 2026.
- Plotly’s independent evaluation gave K3.1 Pro 42 of 43 data-analysis tasks.
What is Kimi K3.1 Pro?
Kimi K3.1 Pro is Moonshot AI’s first model in its K3.1 series and the company’s most capable 3T-class open-weight model to date, according to Moonshot AI. The launch expands the Kimi family with a model positioned for long-context work, reasoning, coding, and tool-based tasks rather than short conversational prompts alone.
Moonshot AI introduced Kimi K3.1 Pro on October 24, 2026, alongside Kimi K3.1 Pro Highspeed. The standard model provides a 1-million-token context window, which means developers can place a very large amount of source material into a single model request when the application and API limits permit it. Moonshot AI’s launch announcement describes the model as a 3T-class open-weight system and sets out the planned release schedule.
A large context window is useful when an AI system needs to reference extensive codebases, lengthy reports, financial documents, video-related inputs, or accumulated task materials. A 1-million-token window does not guarantee that every detail receives equal attention, however. Developers still need to evaluate whether Kimi K3.1 Pro finds relevant information accurately in the middle and end of long inputs.
Kimi K3.1 Pro also arrives during a period when more AI providers are emphasizing autonomous or semi-autonomous workflows. Users comparing models for these tasks can also examine how cheaper agent tools approach speed, cost, and task execution, since a large context window is only one part of an agent system.
Where can developers use Kimi K3.1 Pro now?
Kimi K3.1 Pro is available immediately through Kimi.ai, Kimi Work, Kimi Code, and Moonshot AI’s API. The immediate availability matters because developers can test the model before the planned full-weight release and decide whether its context length, reasoning behavior, and performance fit an existing application.
Kimi K3.1 Pro is also available through Vercel AI Gateway, which added both the standard and Highspeed variants on October 23, 2026. Vercel describes the standard model as retaining K3’s 1-million-token context and identifies coding, 3D modeling, financial analysis, and agentic work as intended use cases. Vercel’s availability announcement provides the platform-specific access details.
API access does not eliminate the need for implementation testing. A model can perform well in a general demonstration yet behave differently when connected to a company’s documents, retrieval system, tools, permissions, and output rules. The practical response is to begin with limited, non-sensitive evaluation data and measure task completion, output quality, latency, and cost before expanding access.
Developers should also define which data the model is allowed to receive. Long-context systems can make it easier to submit large collections of files, but that convenience increases the importance of reviewing data handling rules, internal permissions, and prompt construction before a production deployment.
How does Kimi K3.1 Pro handle reasoning and inputs?
Kimi K3.1 Pro supports text, image, and video input, and its API documentation says reasoning is always enabled. The documentation also says the API defaults to “max” reasoning effort, which means developers should account for the model’s reasoning configuration when assessing response speed and usage costs.
Kimi K3.1 Pro’s multimodal input support allows an application to provide more than written material in the same workflow. A coding or analysis tool could use text instructions alongside images or video-related information, depending on how the developer designs the application. The useful limit is that multimodal input support does not establish accuracy for every task type, so outputs still require evaluation against the source material.
The Kimi API documentation identifies the access requirements and model behavior for K3.1 Pro. Moonshot AI’s Kimi API quickstart states that reasoning remains enabled and defaults to the maximum setting. That configuration can help with complex tasks, but it can also make a direct comparison with a non-reasoning model incomplete unless the testing setup is clear.
For most teams, the sensible approach is to separate simple requests from tasks that genuinely need extended reasoning. A concise classification task may not need the same configuration as a multi-step code review, document analysis, or agent workflow that must use tools and reconcile many source files.
What do Kimi K3.1 Pro benchmarks show?
Kimi K3.1 Pro has strong early benchmark claims, but Moonshot AI’s comparisons remain self-reported and should not be treated as independent proof of overall superiority. Moonshot says K3.1 Pro scored 65.7% on Terminal-Bench 4.0, compared with 66.4% for Claude Opus 5.5 and 58.2% for GPT-6 Astra in the company’s comparison.
Kimi K3.1 Pro also scored 92.7% with tools on BenchCAD, according to Moonshot AI. BenchCAD is a benchmark for 3D reconstruction and CAD-code work, so the result is most relevant to developers evaluating model-assisted design, geometry, and related tool-use workflows. A single benchmark does not predict results across every coding, analysis, writing, or agent task.
| Evaluation | Kimi K3.1 Pro result | Source type | What the result can show |
|---|---|---|---|
| Terminal-Bench 4.0 | 65.7% | Moonshot AI, self-reported | Performance in the company’s terminal-task comparison |
| BenchCAD with tools | 92.7% | Moonshot AI, self-reported | Performance on 3D reconstruction and CAD-code tasks |
| Plotly data-analysis evaluation | 42 of 43 tasks | Independent evaluation | Performance on Plotly’s launch-day data-analysis task set |
Plotly’s independent evaluation gave Kimi K3.1 Pro 42 of 43 data-analysis tasks, compared with 35 of 43 for Kimi K3. The run cost $13.47 and had a median completion time of 2.5 minutes. Plotly’s benchmark report is a more useful reference for users who want a disclosed evaluation outside Moonshot AI’s own launch material.
How does Kimi K3.1 Pro Highspeed differ from the standard model?
Kimi K3.1 Pro Highspeed is the faster K3.1 variant, and Moonshot AI advertises it at two to three times the standard model’s speed. The speed claim matters most for interactive coding tools, repeated agent steps, and workflows where waiting for a model response interrupts a person’s work.
Kimi K3.1 Pro Highspeed and the standard Kimi K3.1 Pro model are both available through Moonshot AI’s named products and API. Moonshot’s published launch details do not establish that the faster variant is the best choice for every task, because a speed comparison alone does not show how performance, output consistency, reasoning quality, or cost differ across individual workloads.
The practical comparison should start with a representative task set. Teams can send identical prompts, documents, tool calls, and evaluation criteria to each version, then compare completion time and output quality. Developers should avoid choosing a faster model solely from a vendor speed claim when a workflow requires careful reasoning or reliable use of external tools.
Speed also changes how users experience AI agents. A faster response can make an agent feel more practical, but speed does not make permissions safer or outputs more trustworthy. Users should retain review steps when an AI system drafts code, analyzes business material, or takes actions through connected tools.
When will Kimi K3.1 Pro open weights be released?
Kimi K3.1 Pro’s full weights are planned for release by November 4, 2026, according to Moonshot AI. The planned open-weight release could give developers more options for experimenting with deployment environments and model customization than API-only access provides.
Open weights do not automatically make a model simple to run. A local or self-managed deployment still requires appropriate hardware, infrastructure, security controls, storage, model-serving software, and operational expertise. Developers should wait for Moonshot AI’s release materials before assuming the exact hardware needs, license terms, or deployment conditions.
Kimi K3.1 Pro’s planned release is relevant to organizations that prefer greater control over where model inference occurs. That preference has become more important as some AI services gain deeper access to user content, including systems that connect email and photo data to in-car assistants. Readers considering those tradeoffs can review how connected personal data can expand an AI assistant’s usefulness while raising more privacy questions.
The most sensible action is to treat the November 4 date as a stated plan rather than a completed release. Teams that need open weights for a project should confirm that the files, documentation, license, and technical requirements are available before committing to a deployment schedule.
Who should consider using Kimi K3.1 Pro?
Kimi K3.1 Pro is most relevant to developers and organizations that need a large context window, multimodal input, default reasoning, or an eventual open-weight option. The model may be especially worth evaluating for coding, data analysis, 3D-related work, financial analysis, and agentic tasks, based on Moonshot AI and Vercel’s stated use cases.
Kimi K3.1 Pro is less compelling for users who only need brief chat responses or who cannot evaluate model output before relying on it. A 1-million-token context window can be valuable for complex source material, but it does not remove the need for human review, especially when outputs influence business decisions, software changes, or sensitive information.
AI agents require additional caution when they can access websites, accounts, files, or tools. Recent research coverage has shown that AI agents can be used in attacks against online services, which is why agent security controls should be part of model testing from the beginning. Limit credentials, require approval for consequential actions, and test with non-sensitive accounts before connecting a model to production systems.
Kimi K3.1 Pro is best viewed as a new option to benchmark against a team’s existing model stack. The direct next step is to test the standard and Highspeed versions on a small set of real, permitted tasks, document the results, and reassess after Moonshot AI publishes the promised open weights.
FAQ
Is Kimi K3.1 Pro available now?
Kimi K3.1 Pro is available now through Kimi.ai, Kimi Work, Kimi Code, and Moonshot AI’s API. Vercel AI Gateway also added Kimi K3.1 Pro and Kimi K3.1 Pro Highspeed on October 23, 2026.
How large is Kimi K3.1 Pro’s context window?
Kimi K3.1 Pro has a 1-million-token context window. The large window can support extensive source material, but developers still need to test whether the model retrieves and uses important information accurately.
Does Kimi K3.1 Pro support images and video?
Kimi K3.1 Pro supports text, image, and video input. Moonshot AI’s API documentation also says reasoning is always enabled and defaults to maximum reasoning effort.
Are Kimi K3.1 Pro benchmark scores independently verified?
No, Moonshot AI’s Terminal-Bench 4.0 and BenchCAD scores are self-reported vendor claims. Plotly published an independent launch-day data-analysis evaluation that gave Kimi K3.1 Pro 42 of 43 tasks.
When are Kimi K3.1 Pro’s full weights expected?
Kimi K3.1 Pro’s full weights are planned for release by November 4, 2026. Developers should confirm the release materials, license, and deployment requirements when Moonshot AI publishes them.