LLMPrivate

Kimi K3 Fast

Fast-inference variant of Moonshot's 2.8T-parameter Kimi K3, optimized for low-latency multimodal reasoning and agentic workflows with 1M context.

Maker
Moonshot AI
Modality
Text + vision
Context
1,000K tokens
Open weights
Yes — Apache-style license

Overview

What is Kimi K3 Fast

Kimi K3 Fast is a fast-inference variant of Moonshot AI's Kimi K3 model, released on July 27, 2026. It delivers the same 2.8-trillion-parameter multimodal intelligence as the base K3 but optimized for lower latency, making it ideal for real-time agentic coding, vision tasks, and long-horizon reasoning within a 1-million-token context window.

Running it privately on Venice

On Venice, Kimi K3 Fast runs with zero retention — your prompts are never stored, profiled, or used for training. This means you get the full power of a frontier multimodal model with private, end-to-end uncensored access, ideal for sensitive coding, research, or enterprise workflows where data sovereignty matters. The model's open weights and Venice's permissionless infrastructure ensure full compliance without sacrificing performance.

Private (zero retention)No prompt trainingTEE · hardware enclaveEnd-to-end encrypted

Assessment

Strengths and limitations

Strengths
  • Massive 1-million-token context window enables processing of entire codebases, books, or long video transcripts in a single pass.
  • Native multimodal vision and reasoning capabilities support image input, PDF analysis, and complex agentic workflows.
  • Optimized for low-latency inference, making it suitable for real-time coding agents, interactive research, and dynamic planning.
  • Open weights allow for transparency and future self-hosting or fine-tuning options, unlike closed rivals.
  • Supports tool use, web search, and structured JSON output, enabling robust agent frameworks and API integrations.
Limitations
  • Higher output cost at $22.50 per million tokens makes sustained generation expensive compared to cheaper open models.
  • No end-to-end encryption or TEE protection on Venice, limiting use in highly regulated environments despite zero retention.
  • Vision output is text-only: cannot generate or edit images, only interpret them.
  • Still new: lacks third-party benchmark validation and real-world stress testing across diverse domains.

Capabilities

What it supports

  • Tool use / function calling
  • Vision (image input)
  • Reasoning
  • Web search
  • Code-optimized
  • Structured output (JSON schema)
  • Audio input
  • Video input
  • Multiple image inputs
  • Log probabilities

Specifications

Datasheet

Maker
Moonshot AI
Released
July 27, 2026
Architecture
Stable LatentMoE with Kimi Delta Attention (KDA) and Attention Residuals (AttnRes)
Parameters
2.8 trillion (total), 16 of 896 experts active per token
Open weights
Yes — Apache-style license
Context window
1,000K tokens
Max output
131.072K tokens
Capabilities
Vision, Function calling, Reasoning, Web search, Code-optimized
Privacy on Venice
Private — zero retention
Available on Venice since
Aug 2026
License
Other

API

Call it from your code

Venice exposes an OpenAI-compatible API. Point your base URL at Venice and pass the model id.

curl https://api.venice.ai/api/v1/chat/completions \
  -H "Authorization: Bearer $VENICE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "kimi-k3-fast-api",
    "messages": [{ "role": "user", "content": "Explain quantum tunneling simply." }]
  }'

Pricing

What it costs on Venice

Billed per token on Venice: $4.50 per 1M input tokens and $22.50 per 1M output tokens.

Input / 1M tokens
$4.50
Per 1M tokens
Output / 1M tokens
$22.50
Per 1M tokens
Cached input / 1M
$0.45
Per 1M tokens

New Venice accounts include a free daily allowance and 500 welcome credits — no credit card required.

Alternatives

How it compares

ModelMax resolutionStrongest atOpen weightsPrice (Venice)
Kimi K3 FastN/ALong-context agentic coding, multimodal reasoningYes$4.50 in · $22.50 out / 1M
Claude Opus 5N/AHigh-stakes reasoning, enterprise safetyNo$6 in · $30 out / 1M
DeepSeek V4 Flash 0731N/ASpeed and cost efficiencyYes$0.17 in · $0.35 out / 1M
Gemini 3.7 FlashN/AGoogle ecosystem integrationNo$1.88 in · $9.38 out / 1M

Fast variant of the open 2.8T Kimi K3 with 1M context and vision.

Use cases

What it is good for

  1. 01Autonomous coding agents that navigate and modify large repositories with minimal latency.
  2. 02Long-document analysis and summarization, including legal contracts, research papers, and financial reports.
  3. 03Multimodal research workflows combining text, images, and web search for interactive dashboards.
  4. 04Enterprise automation where data privacy and uncensored reasoning are required.
  5. 05Real-time planning and decision-making in complex simulations or game development.

Prompting

Getting better results

Use explicit structure in prompts — Kimi K3 Fast excels when given clear goals, steps, and expected output formats.

Leverage function calling and web search for up-to-date information or external tool integration.

Break down long tasks into stages to manage output length within the 131K token limit.

Include image or PDF references directly in prompts for vision-augmented reasoning.

Use JSON schema output for reliable parsing in automated pipelines.

Version history

Kimi K2
2025

Predecessor model with smaller context and lower capability.

Kimi K3
2026-07

Base open-weight 2.8T model with 1M context.

Kimi K3 Fast
2026-07

Optimized for low-latency inference, same capabilities.

FAQ

Frequently asked questions

Kimi K3 Fast is a low-latency inference variant of Moonshot AI's 2.8-trillion-parameter Kimi K3 model, released on July 27, 2026. It supports a 1-million-token context window, vision input, tool use, and web search, optimized for real-time agentic workflows in coding, research, and planning.

On Venice, Kimi K3 Fast costs $4.50 per million input tokens and $22.50 per million output tokens. Cached input is significantly cheaper at $0.45 per million tokens, making repeated access to long contexts more affordable.

Kimi K3 Fast is not free, but it is based on open weights released by Moonshot AI under an open license. You can access the model via API on Venice, but cannot self-host it directly — the fast-inference variant is served only via API.

Yes. Kimi K3 Fast supports image and PDF input, enabling multimodal reasoning. It can analyze charts, diagrams, and documents, though it only outputs text — it cannot generate or edit images.

Yes. Kimi K3 Fast supports function calling, web search, structured JSON output, and tool use, making it suitable for building autonomous agents that interact with external systems and APIs.

Kimi K3 Fast supports up to 1 million tokens of context, allowing it to process extremely long documents, codebases, or multimodal inputs in a single session. The maximum output length is 131,072 tokens.

Kimi K3 Fast offers open weights, lower cost, and a larger context window, making it better for long-horizon coding and research. Claude Opus 5 excels in safety, enterprise compliance, and nuanced reasoning but is more expensive and closed. Choose K3 Fast for uncensored, private, agentic work; Opus 5 for regulated or safety-critical tasks.

Run Kimi K3 Fast privately

No prompt logging. No data used for training.