Kimi K3.1 Pro

New

moonshotai/kimi-k3.1-pro-20261023

MoonshotAI's Kimi K3.1 Pro model processes text, image, and video inputs to generate text outputs. It supports a context length of 1,048,576 tokens and features tool use and reasoning capabilities. Pricing is set at $2 per million input tokens and $10 per million output tokens.

  • tool use
  • structured outputs
  • reasoning

At a glance

providermoonshotai
releasedOct 23, 2026
context1.0M
input / M$2

Specifications

What the API gives you

Context window
1.0M tokens
Max output
944K tokens
Input price
$2 / 1M tokens
Output price
$10 / 1M tokens
Cache read
$0.20 / 1M tokens
Modalities
text, image, video → text
Knowledge cutoff
—
Released
Oct 23, 2026

Measured evidence

Public benchmark record

Design Arena Coding
1356 Elo2026-10-25
Design Arena UI
1376 Elo2026-10-25
Design Arena Website
1332 Elo2026-10-25
LMArena WebDev‡
1692 Elo2026-10-23max effort

LMArena data licensed CC-BY-4.0. Aider (Apache-2.0) and SWE-bench (MIT) are open. Design Arena uses blind human preference. ‡ Submitted scaffold plus model result. Compare the harness and effort settings, not only the model name.

Task evidence

How broad is the support?

Each status is exact to this model version and the selected task. Official release claims remain provisional.

  • Best LLM for Frontend & UIEstablished evidence

    82% of intended weighted task evidence across 2 independent sources. 6 of 6 configured evaluation feeds currently have results.

  • Best LLM for CodingEstablished evidence

    36% of intended weighted task evidence across 2 independent sources. 7 of 7 configured evaluation feeds currently have results.

  • Best LLM for Code CompletionProvisional evidence

    36% of intended weighted task evidence across 1 independent source; broader independent confirmation is still missing from Aider Polyglot or LiveBench Coding. 3 of 3 configured evaluation feeds currently have results.

  • Best Local LLM for CodingProvisional evidence

    21% of intended weighted task evidence across 1 independent source; broader independent confirmation is still missing from Aider Polyglot or LiveBench Coding. 4 of 4 configured evaluation feeds currently have results.

  • Best LLM for Debugging & Code ReviewProvisional evidence

    17% of intended weighted task evidence across 1 independent source; broader independent confirmation is still missing from Aider Polyglot or LiveBench Coding. 5 of 5 configured evaluation feeds currently have results.

Recommendation coverage

Where this model appears

  1. #3Best LLM for Frontend & UI
  2. #3Best LLM for Coding

Catalog data via OpenRouter and models.dev. Last checked within the past 6 hours.