Using Qwen3-Coder-480B-A35B-Instruct on AWS Bedrock
Implementation guide · Qwen3-Coder · Alibaba
AWS Bedrock exposes Qwen3-Coder-480B-A35B-Instruct through model ID qwen3-coder-480b-a35b-instruct. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.
Last refreshed 2026-06-19. Next refresh: weekly.
Quick Start
- 1
- 2Use the AWS Bedrock SDK or REST API to call
qwen3-coder-480b-a35b-instruct— see the documentation for request format.
Code Examples
pip install boto3AWS_ACCESS_KEY_IDqwen3-coder-480b-a35b-instructUse 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="qwen3-coder-480b-a35b-instruct",
messages=[{
"role": "user",
"content": [{"text": "Hello"}]
}]
)
print(response["output"]["message"]["content"][0]["text"])Pricing on AWS Bedrock
Capabilities
About Qwen3-Coder-480B-A35B-Instruct
Qwen3-Coder-480B-A35B-Instruct is Alibaba's flagship open-source code generation and agentic model, released July 22, 2025 under the Apache 2.0 license. The model has 480 billion total parameters with 35 billion active parameters per token, organized across 62 transformer layers with 160 specialized expert networks and 8 experts activated per token. It uses Grouped Query Attention (GQA) with 96 query heads and 8 key-value heads and supports a native context window of 262,144 tokens, extendable to 1 million tokens via YaRN position scaling.