Using Kimi K2 Thinking on AWS Bedrock
Implementation guide · Kimi K2 · Moonshot AI
ServerlessOpen Source
AWS Bedrock exposes Kimi K2 Thinking through model ID kimi-k2-thinking. 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
- 2Use the AWS Bedrock SDK or REST API to call
kimi-k2-thinking— see the documentation for request format. - 3
Code Examples
Install
pip install boto3API key
AWS_ACCESS_KEY_IDModel ID
kimi-k2-thinkingUse Amazon Bedrock model IDs, e.g. "anthropic.claude-3-opus-20240229-v1:0" for on-demand, or cross-region inference profile IDs like "us.anthropic.claude-opus-4-7-20251101-v1:0". These differ from the public model slug.
import boto3
# Reads AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_DEFAULT_REGION from env
client = boto3.client("bedrock-runtime", region_name="us-east-1")
response = client.converse(
modelId="kimi-k2-thinking",
messages=[{
"role": "user",
"content": [{"text": "Hello"}]
}]
)
print(response["output"]["message"]["content"][0]["text"])Pricing on AWS Bedrock
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.60 |
| Output tokens | $2.50 |
Capabilities
ReasoningStructured Outputs
About Kimi K2 Thinking
Extended thinking variant of Kimi K2 with native reasoning capabilities. 256K context.
Model Specs
Released2025-01-01
Parameters1T (32B active)
Context256k
ArchitectureDecoder Only