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Moonshot: Kimi K3.1 Pro

kimi-k3.1-pro

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Kimi K3.1 Pro is a multimodal reasoning model for coding, 3D creation, document analysis and multi-step tool use. It supports a 1M-token context window and text, image and video inputs. Reasoning is always enabled, with low, high and max effort levels.

Modalities

Text + Image + Video → Text

Input / output price

$2.60 / $13.00 per 1M

Context

1.05M

Capabilities

ReasoningVisionTool callingLong context

Pricing

Billed per token actually used and deducted from your credits.

ItemUSD per 1M tokens
Input$2.60
Output$13.00
Cached input$0.260

Calculator

Drag the sliders to estimate what this model will cost.

Per request
$0.0182
Per day
$9.10
Per month (30 days)
$273.00

Kimi K3.1 Pro: input $2.6/M · output $13/M · cached input $0.26/M

Request with these settings
curl https://api.geniusrelaygpt.com/v1/chat/completions \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "kimi-k3.1-pro", "max_tokens": 800,
       "messages": [{"role": "user", "content": "…"}]}'

Code samples

OpenAI-compatible. Set the base URL to https://api.geniusrelaygpt.com/v1 and the model to kimi-k3.1-pro.

curl https://api.geniusrelaygpt.com/v1/chat/completions \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "kimi-k3.1-pro",
    "stream": true,
    "messages": [{"role": "user", "content": "Hello"}]
  }'

Use it in a client: Cursor · Cline · SillyTavern · Codex

Parameters

Common OpenAI parameters can be passed as-is.

temperaturetop_pmax_tokensstreamstoppresence_penaltyfrequency_penaltyseed

FAQ

How is Kimi K3.1 Pro billed?
Input is $2.60 and output is $13.00 per million tokens; cached input is $0.260. The charge for every request is listed in Usage Logs in the console.
How long is the context window?
1.05M tokens. In a long conversation every turn is billed for the full input, so keep the history under control.
Does it support streaming?
Yes. Add "stream": true to the request to receive server-sent events in the OpenAI format.