Now on VeniceLLMReasoningAnonymous

Kimi K3.1 Pro Highspeed

Moonshot's fastest frontier-class model — K3.1 Pro quality at 2–3× the speed, with a 1M-token context, vision, tool use and web search.

For agents
curl https://api.venice.ai/api/v1/chat/completions \
  -H "Authorization: Bearer $VENICE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "kimi-k3-1-pro-highspeed",
    "messages": [{ "role": "user", "content": "Explain quantum tunneling simply." }]
  }'
Model IDkimi-k3-1-pro-highspeed
Maker
Moonshot AI
Context
1,000K tokens
Reasoning
Supported
Privacy
Anonymous

Overview

What is Kimi K3.1 Pro Highspeed

Kimi K3.1 Pro Highspeed is Moonshot AI's high-speed variant of Kimi K3.1 Pro, a 3T-class frontier model released October 23, 2026. It delivers identical quality to K3.1 Pro at roughly 2–3× the speed, with a 1M-token context window, vision input, tool use, web search and always-on reasoning.

Using it anonymously on Venice

On Venice, Kimi K3.1 Pro Highspeed runs under the anonymized privacy tier — your prompts are not stored, profiled, or used for training. You get frontier reasoning and coding without feeding a Big-Tech profile, billed per token with no subscription. Note that this variant is not uncensored, and Venice does not run it in a TEE or with end-to-end encryption — the privacy guarantee is zero retention of prompts.

AnonymousNo prompt trainingTEE · hardware enclaveEnd-to-end encrypted

Agent quickstart

Three calls, copied straight out

The API is OpenAI-compatible: change the base URL and the model id and existing client code works unchanged.

Streaming chat

curl https://api.venice.ai/api/v1/chat/completions \
  -H "Authorization: Bearer $VENICE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "kimi-k3-1-pro-highspeed",
    "stream": true,
    "messages": [{ "role": "user", "content": "Draft the release note." }]
  }'

Tool calling

curl https://api.venice.ai/api/v1/chat/completions \
  -H "Authorization: Bearer $VENICE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "kimi-k3-1-pro-highspeed",
    "messages": [{ "role": "user", "content": "Find the rate limits." }],
    "tools": [{
      "type": "function",
      "function": {
        "name": "search_docs",
        "description": "Search the API documentation.",
        "parameters": {
          "type": "object",
          "properties": { "query": { "type": "string" } },
          "required": ["query"]
        }
      }
    }],
    "tool_choice": "auto"
  }'

Python SDK

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["VENICE_API_KEY"],
    base_url="https://api.venice.ai/api/v1",
)

resp = client.chat.completions.create(
    model="kimi-k3-1-pro-highspeed",
    messages=[{"role": "user", "content": "Build without permission."}],
)
print(resp.choices[0].message.content)

Specifications

Datasheet

Maker
Moonshot AI
Open weights
No — proprietary at launch; Moonshot says full weights release by Nov 4, 2026
License
Proprietary today — Moonshot states full model weights will be released by Nov 4, 2026
Modes
Thinking mode only — reasoning levels low / high / max, with max as the default; disabling thinking is rejected
Context window
1,000K tokens
Released
October 23, 2026
Architecture
3T-class model; post-trained version of Kimi K3 with substantially larger post-training compute (large-scale joint RL across hundreds of domains)
Variant
Highspeed build of Kimi K3.1 Pro — identical model quality, approximately 2–3× the output speed
Max output
128K tokens
Capabilities
Vision, Function calling, Reasoning, Web search, Code-optimized
Privacy on Venice
Anonymized — prompts not stored
Available on Venice since
Oct 2026

Assessment

Strengths and limitations

Strengths
  • Frontier-level coding and agentic performance: Moonshot reports 65.7% on Terminal-Bench 4.0, ahead of GPT-6 Astra (58.2%) and narrowly behind Claude Opus 5.5 (66.4%).
  • 2–3× the speed of standard K3.1 Pro with identical model quality — built for interactive coding sessions and chat where latency matters.
  • 1M-token context window for whole-repo code analysis, long documents, and long-horizon agent runs.
  • Full agent stack: tool use / function calling, vision (including multiple image inputs), web search, structured JSON output, and code-optimized behavior.
  • Strong price-to-intelligence ratio: Moonshot prices the base model at parity with GPT-6.1 Sol and half of Claude Opus 5.5.
Limitations
  • Reasoning cannot be disabled: the model only supports thinking mode, and the reasoning trace inflates output tokens you pay for.
  • Not open weights at launch; the promised open release is dated Nov 4, 2026, so self-hosting is not possible today.
  • Highspeed costs roughly twice the standard K3.1 Pro rate for the same quality — you pay a premium purely for latency.
  • Not uncensored: it is a standard aligned commercial model, so Venice's uncensored positioning does not apply here.
  • Sampling settings are fixed (e.g. temperature is locked), which limits fine-grained output control.

Use cases

What it is good for

  1. 01Interactive coding sessions and pair-programming where response latency matters.
  2. 02Long-horizon coding agents working across entire repositories within the 1M-token window.
  3. 03Financial research and document analysis over very large context sets.
  4. 043D creation and front-end generation from written briefs.
  5. 05Multi-step agentic workflows combining tool calls, image understanding, and web search.

Prompting

Getting better results

Leave thinking enabled and set reasoning effort to "low" for quick turns — "max" is the default and burns the most output tokens.

Start a fresh session rather than switching to this model mid-conversation from a K3-series or K2.x session; switching degrades quality and cache hits.

Use Venice's cached input rate ($0.60/1M) by keeping your system prompt and long reference material stable across calls.

Paste whole files or large codebases up to the 1M-token window instead of summarizing — long-context retrieval is one of its edges.

Attach multiple screenshots or diagrams in one request; multi-image input is supported for code review and UI work.

Ask for structured JSON with an explicit schema when building agents — structured output is a first-class capability.

Alternatives

How it compares

ModelBest forContextOpen weightsPrice (Venice)
Kimi K3.1 Pro HighspeedFast frontier coding & agents1M tokensNo$6 in · $30 out / 1M
Kimi K3Open-weights frontier work1M tokensYes$3.75 in · $18.75 out / 1M
Gemini 3.8 FlashCheap fast general chat1M tokensNo$0.94 in · $4.69 out / 1M
Qwen 3.8 MaxBudget long-context reasoning1M tokensNo$2.50 in · $7.50 out / 1M

Pick Kimi K3.1 Pro Highspeed for interactive frontier coding and agentic runs where latency is felt by a human; drop to Qwen 3.8 Max or Gemini 3.8 Flash when cost dominates, or to Kimi K3 when open weights are non-negotiable.

Pricing

What it costs on Venice

Billed per token on Venice: $6 per 1M input tokens and $30 per 1M output tokens.

Input / 1M tokens
$6
Per 1M tokens
Output / 1M tokens
$30
Per 1M tokens
Cached input / 1M
$0.60
Per 1M tokens

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

Getting a key

From nothing to a first call

  1. 01

    Create a key in API settings. Nothing else is required to start.

  2. 02

    Export it as VENICE_API_KEY so the snippets above run unedited.

  3. 03

    Point an existing OpenAI client at https://api.venice.ai/api/v1. The scheme is part of the value: an OpenAI client given a bare host does not resolve it.

  4. 04

    Pass kimi-k3-1-pro-highspeed as the model and send the request.

FAQ

Frequently asked questions

Kimi K3.1 Pro Highspeed is Moonshot AI's accelerated variant of Kimi K3.1 Pro, launched October 23, 2026. It offers identical model quality to K3.1 Pro at approximately 2–3× the speed, with a 1M-token context window, vision input, tool use, web search, and always-on reasoning.

Venice bills it per token: $6 per 1M input tokens, $30 per 1M output tokens, and $0.60 per 1M cached input tokens. There is no subscription required — you pay only for what you use.

Not yet. The model launched as proprietary on October 23, 2026, but Moonshot has stated that full model weights will be released by November 4, 2026. Until then it cannot be self-hosted or fine-tuned; Kimi K3 is the open-weights alternative on Venice.

They are the same model with the same quality; Highspeed is simply 2–3× faster. Choose Highspeed for interactive coding or chat where you watch the output arrive, and standard K3.1 Pro for unattended batch or agent runs where latency doesn't matter and the lower rate does.

Yes. It supports function calling / tool use, image input including multiple images per request, structured JSON output, web search, and code-optimized responses — the full agentic stack.

No. The K3.1 Pro series only supports thinking mode, with reasoning levels of low, high, and max — max is the default. Requests that disable thinking are rejected, so budget for reasoning tokens in your output costs.

Venice runs it under the anonymized privacy tier: prompts are not stored, profiled, or used for training. Note that this model is not run in a trusted execution environment and the traffic is not end-to-end encrypted — the guarantee is zero retention of your prompts.

1,000K tokens (1 million), with up to 128K tokens of output per response — enough for entire codebases, long financial documents, or multi-hour agent transcripts in a single context.

Use Kimi K3.1 Pro Highspeed anonymously

One key, free to start, no credit card.

Start chat