Using Qwen3-Coder-Next on AWS Bedrock
Implementation guide · Qwen3-Coder · Alibaba
AWS Bedrock exposes Qwen3-Coder-Next through model ID qwen3-coder-next. 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-next— see the documentation for request format. - 3
Code Examples
pip install boto3AWS_ACCESS_KEY_IDqwen3-coder-nextUse 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-next",
messages=[{
"role": "user",
"content": [{"text": "Hello"}]
}]
)
print(response["output"]["message"]["content"][0]["text"])Pricing on AWS Bedrock
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.50 |
| Output tokens | $1.20 |
Capabilities
About Qwen3-Coder-Next
Qwen3-Coder-Next is an ultra-sparse Mixture-of-Experts coding agent model from Alibaba's Qwen team, released February 3, 2026 under Apache 2.0. It has 80B total parameters with 3B active at inference, delivering substantially higher throughput than comparable dense models. It supports a native 256K context window, function calling, structured outputs, Claude Code, Qwen Code, Cline, Kilo, and other scaffold templates. Benchmarks reported in the DAT-3724 datapack include SWE-Bench Pro 44.3%, SWE-Bench Resolved 70.6%, and TerminalBench 2 36.2%.