Using Qwen3-Coder-30B-A3B-Instruct on AWS Bedrock
Implementation guide · Qwen3-Coder · Alibaba
AWS Bedrock exposes Qwen3-Coder-30B-A3B-Instruct through model ID qwen3-coder-30b-a3b. 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-30b-a3b— see the documentation for request format. - 3
Code Examples
pip install boto3AWS_ACCESS_KEY_IDqwen3-coder-30b-a3bUse 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-30b-a3b",
messages=[{
"role": "user",
"content": [{"text": "Hello"}]
}]
)
print(response["output"]["message"]["content"][0]["text"])Pricing on AWS Bedrock
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.15 |
| Output tokens | $0.62 |
Capabilities
About Qwen3-Coder-30B-A3B-Instruct
Qwen3-Coder-30B-A3B-Instruct is Alibaba's efficient open-source code generation model in the Qwen3-Coder family, released December 3, 2025 under the Apache 2.0 license. The model has 30.5 billion total parameters with 3.3 billion active per forward pass, organized across 48 transformer layers with 128 experts and 8 activated per token. It uses Grouped Query Attention (GQA) with 32 query heads and 4 key-value heads. Native context window is 262,144 tokens, extendable to 1 million tokens via YaRN. The model supports multi-turn tool calling, function calling, repository-level code understanding, and structured outputs.