Kimi K3.1 Pro is Moonshot AI’s flagship multimodal reasoning model for long-context coding, autonomous agents, financial analysis, 3D creation, and advanced knowledge work.
The Kimi K3.1 Pro family includes two versions:
kimi-k3.1-prokimi-k3.1-pro-highspeed
Both versions offer the same core capabilities. The Highspeed version is optimized for faster output and provides approximately 2–3× higher response speed.
Technical specifications of Kimi K3.1 Pro
| Item | Publicly documented details |
|---|---|
| Model ID (Kimi Code) | k3.1-pro |
| Provider | Moonshot AI (Kimi) |
| Model family | K3.1; post-trained version of Kimi K3 |
| Model scale | Described by Moonshot AI as a 3T-class model; the technical blog does not state a more precise active-parameter count |
| Context window | Up to 1,048,576 tokens (1M) on eligible plans; some Kimi Code tiers are limited to 256K |
| Input modalities | Text, images, and video are described in official model/platform materials; availability can depend on the API/product surface |
| Output | Primarily text, including code and structured responses |
| Reasoning mode | Required; low, high, and max effort levels; max is the default in Kimi Code |
| Release announcement | 2026-10-23/24 |
| Related model | k3.1-pro-highspeed, advertised as the same capability with approximately 2–3× faster output |
Actual limits and availability may vary by plan, endpoint, and API provider.
What Is Kimi K3.1 Pro & Kimi K3.1 Pro Highspeed?
Kimi K3.1 Pro and Kimi K3.1 Pro Highspeed are two serving variants of Moonshot AI’s flagship K3.1 Pro multimodal reasoning model. Both versions are designed for complex coding, autonomous agents, financial analysis, 3D creation, and long-context knowledge work.
The two variants share the same underlying model capabilities, architecture, context window, reasoning features, and multimodal inputs. The main distinction is serving speed: Kimi K3.1 Pro Highspeed delivers approximately 2–3× faster output than the standard Kimi K3.1 Pro model.
Both versions use a Mixture-of-Experts architecture with approximately 2.8 trillion total parameters and 104 billion active parameters. They support up to 1 million tokens of context and accept text, image, and video inputs.
The standard version is better suited to quota-conscious and asynchronous workloads, while the Highspeed version is intended for interactive applications where shorter response times are important.
Main Features of Kimi K3.1 Pro
- Long-context reasoning: Both variants support up to 1M tokens and always-on thinking, with
low,high, andmaxreasoning levels for large repositories, complex documents, and long-running tasks. - Multimodal understanding: They process text, images, and video, making them suitable for visual analysis, document workflows, and creative applications.
- Agentic coding and tool use: The models can plan multi-step tasks, work across repositories, call tools, debug code, and execute extended software workflows.
- 3D, CAD, and financial workflows: They support Blender and CAD scripting, parametric modeling, spreadsheet analysis, financial modeling, investment research, and cross-document verification.
- Structured API capabilities: Both versions support streaming, function calling, JSON schema output, partial mode, dynamic tool loading, and context caching with 5-minute or 1-hour TTL options.
- Highspeed inference: Kimi K3.1 Pro Highspeed provides the same core capabilities as Kimi K3.1 Pro while generating output approximately 2–3× faster. It is designed for interactive applications and may consume about twice the quota.
Benchmark Performance of Kimi K3.1 Pro
Moonshot AI publishes benchmark results for Kimi K3.1 Pro. The company describes the Highspeed version as capability-equivalent to the standard model, but does not publish a separate benchmark table for Highspeed.
Therefore, the results below represent the K3.1 Pro model family. They should be treated as shared capability results rather than independently verified Highspeed scores.
| Benchmark | Kimi K3.1 Pro / Kimi K3.1 Pro Highspeed |
|---|---|
| Terminal-Bench 4.0 | 65.70% |
| Kimi Code Bench 3.0 Long-horizon | 61.20% |
| BenchCAD with tools | 92.70% |
| OfficeQA Pro v2 | 64.4 |
| Business Operation | 37 |
| Financial Modelling improvement over Kimi K3 | 14% |
| Financial Research improvement over Kimi K3 | 20% |
On Terminal-Bench 4.0, Kimi K3.1 Pro scored 65.7%, compared with 58.2% for GPT-6 Astra and 66.4% for Claude Opus 5.5.
Moonshot AI also reports a reduction in factual errors on a targeted financial stress-test set, with the single-claim error rate decreasing from 23.35% for Kimi K3 to 6.85% for Kimi K3.1 Pro.
Kimi K3.1 Pro Highspeed has the same underlying capabilities.
Benchmark results depend on prompts, tools, evaluation settings, and model configuration. Developers should test both serving variants against their own workloads.
Comparison: Kimi K3.1 Pro vs Kimi K3.1 Pro Highspeed vs Kimi K3
| Model | Context | Reasoning | Speed | Input | Open Weights | Best Fit |
|---|---|---|---|---|---|---|
| Kimi K3.1 Pro | Up to 1M | Always on; low, high, max | Standard | Text, images, video | Planned | Complex coding, finance, research, and long-horizon agents |
| Kimi K3.1 Pro Highspeed | Up to 1M | Same as K3.1 Pro | 2–3× faster | Text, images, video | Planned | Interactive assistants and latency-sensitive applications |
| Kimi K3 | Up to 1M | Always on; low, high, max | Standard | Text, images, video | Available | Self-hosting, customization, coding, and multimodal applications |
Kimi K3 is the preceding open-weight model. It is based on Kimi Delta Attention, Attention Residuals, and a sparse Mixture-of-Experts architecture.
Kimi K3.1 Pro is better suited to users who want the latest hosted model and improvements in financial analysis, 3D workflows, and long-horizon agents.
Kimi K3 may be preferable for teams that need downloadable weights, fine-tuning, self-hosting, or deployment through inference engines such as vLLM, SGLang, and TokenSpeed.
Recommended Use Cases
Repository-scale engineering: Analyze large codebases, implement multi-file changes, debug failures, and review pull requests.
Autonomous coding agents: Plan tasks, call tools, execute commands, inspect results, and iterate toward completion.
Game and web development: Work with Unity, Unreal Engine, Godot, Three.js, and browser-based applications.
3D and CAD automation: Generate modeling scripts, reconstruct objects from references, and create parametric assets.
Financial modeling: Support DCF and LBO analysis, spreadsheet automation, investment research, and document verification.
Long-document analysis: Process technical specifications, annual reports, legal documents, and large research collections.
Interactive AI products: Use the Highspeed variant when users need faster responses from a high-capability reasoning model.
Limitations and Considerations
Thinking cannot be disabled: Both K3.1 Pro versions require thinking mode.
Highspeed usage may be higher: The Highspeed version may consume approximately twice the quota of the standard version.
No separate Highspeed benchmark table: Moonshot AI describes Highspeed as capability-equivalent, but separately verified benchmark scores are not currently published.
Complete assistant messages are required: For multi-turn conversations and tool calls, resend the full assistant message, including reasoning and tool-call fields.
Image input format matters: Use the documented structured content format with Base64 image data or supported Kimi file IDs.
Generation parameters may be restricted: Parameters such as temperature, top_p, n, presence_penalty, and frequency_penalty may use fixed or recommended values.
Cache reuse can be affected: Changing reasoning effort or the reusable prompt prefix may reduce context-cache efficiency.
Benchmark results are provider-reported: Published scores may not reflect every programming language, tool environment, or production workload.
Pricing and limits can change: Confirm current API prices, quotas, rate limits, and model availability before deployment.
Kimi K3.1 Pro vs Claude Opus 5.5 vs GPT-6
| Model | Best-fit profile | Context / benchmark evidence | Trade-off |
|---|---|---|---|
| Kimi K3.1 Pro | Complex coding agents, long-context research, analytical workflows | 1M-token context; 65.7% on Moonshot-reported Terminal-Bench 4.0; 42/43 on PlotlyDataAnalyticsBench | Reasoning-heavy tasks may take longer and consume more output tokens |
| Kimi K3 | General flagship tasks where the earlier model is sufficient | 1M-token context; 55.95% on Moonshot's Kimi Code Bench 3.0 Long-horizon; 35/43 on PlotlyDataAnalyticsBench | May be sufficient for simpler work; results are not directly comparable across different benchmark setups |
| Claude Opus 5.5 | High-end coding and complex reasoning alternative | Moonshot's cited Terminal-Bench 4.0 comparison reported 66.4% | The cited comparison is Moonshot-reported; evaluate on your own tasks and API constraints |
| GPT-6 Astra | General-purpose frontier model and coding-agent alternative | Moonshot's cited Terminal-Bench 4.0 comparison reported 58.2% | A single benchmark does not establish overall model superiority |
Choose Kimi K3.1 Pro when a task benefits from a large context, sustained reasoning, and multiple tool interactions. Compare it against alternatives using your own representative prompts, success criteria, latency targets, and total token costs.
How to Access Kimi K3.1 Pro API through CometAPI
Step 1: Create a CometAPI Account
Sign up for or log in to CometAPI and create an API key from the dashboard.
CometAPI provides a unified interface for accessing models from Moonshot AI and other providers, allowing developers to manage model access through one API platform.
Before integrating, check the CometAPI catalog for the current availability, pricing, and supported capabilities of the Kimi K3.1 Pro models.
Step 2: Select a Kimi K3.1 Pro Model
The standard model ID is:
kimi-k3.1-pro
For faster responses, select:
kimi-k3.1-pro-highspeed
Kimi K3.1 Pro is intended for complex reasoning, coding, research, financial analysis, and long-context workflows. The Highspeed version is better suited to interactive applications where response latency is a priority.
Use the exact model identifier shown in the CometAPI model catalog.
Step 3: Send Requests through the CometAPI API
CometAPI provides a unified API layer for supported model providers. Depending on the integration, developers can use its Chat or OpenAI-compatible API format.
Add your prompt or task to the request content field, select the desired Kimi model, and process the returned response in your application.