Using Kimi K2 on GCP Vertex AI

Implementation guide · Kimi K2 · Moonshot AI

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GCP Vertex AI exposes Kimi K2 through model ID kimi-k2. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.

Last refreshed 2026-06-15. Next refresh: weekly.

Quick Start

1
Create an account at GCP Vertex AI and generate an API key.
2
Use the GCP Vertex AI SDK or REST API to call kimi-k2 — see the documentation for request format.
3
You'll be billed $0.50/1M input, $2.00/1M output tokens. See full pricing.

API Portal Documentation Pricing

Code Examples

Install

pip install google-cloud-aiplatform

API key

GOOGLE_CLOUD_PROJECT

Model ID

kimi-k2

For Google-published models use the model name directly, e.g. "gemini-2.0-flash-001". For third-party publishers (Anthropic, Meta, etc.) use the full publisher path, e.g. "publishers/anthropic/models/claude-3-5-sonnet-v2@20241022".

import os
import vertexai
from vertexai.generative_models import GenerativeModel

# Reads GOOGLE_CLOUD_PROJECT from env; authenticates via Application Default Credentials
vertexai.init(project=os.environ["GOOGLE_CLOUD_PROJECT"], location="us-central1")
model = GenerativeModel("kimi-k2")
response = model.generate_content("Hello")
print(response.text)

Pricing on GCP Vertex AI

Type	Price (per 1M)
Input tokens	$0.50
Output tokens	$2.00

Capabilities

JSON / Tool useStructured Outputs

About Kimi K2

Original Kimi K2 model from Moonshot AI. Moonshot discontinued the Kimi K2 series API IDs on 2026-05-25; use kimi-k2-6 as the current successor.

Full model details →

Model Specs

Released2025-07-11

Parameters1K

Context262k

Google Cloud Platform (GCP)

Mountain View, California, United States