Last refreshed 2026-06-19. Next refresh: weekly.
Why use Qwen3-Coder-480B-A35B-Instruct on AWS Bedrock?
AWS Bedrock offers Qwen3-Coder-480B-A35B-Instruct with competitive pricing. AWS Bedrock is Amazon's fully managed foundation-model service, providing unified API access to top models from Anthropic, Meta, Mistral, and other leading AI labs with built-in tools for RAG, fine-tuning, and AI agent development.
Compare Qwen3-Coder-480B-A35B-Instruct across 6 providers to find the best fit for your use caseSetup recipe
Python + curlpip install boto3export AWS_ACCESS_KEY_ID=...import boto3
client = boto3.client("bedrock-runtime", region_name="us-east-1")
response = client.converse(
modelId="qwen3-coder-480b-a35b-instruct",qwen3-coder-480b-a35b-instructRequest example
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"])Gotchas
- Use 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.
- The endpoint template includes a region segment; set the same region in your SDK/client configuration.
- The examples expect AWS_ACCESS_KEY_ID; rename it only if your application config maps the new variable.
Compare Qwen3-Coder-480B-A35B-Instruct Across Providers
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| Fireworks AI | — | — |
| GCP Vertex AI | $0.22 | $1.80 |
| NVIDIA NIM | — | — |
| AWS Bedrock | — | — |
| Vercel AI Gateway | $1.50 | $7.50 |
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. The model is purpose-built for software engineering tasks and agentic workflows: code generation, code review, test writing, multi-step debugging, and browser-based agentic task execution. On release, it achieved state-of-the-art results among open models on Agentic Coding, Agentic Browser-Use, and Agentic Tool-Use benchmarks, with performance comparable to Claude Sonnet 4 on these tasks. Available via Fireworks AI, Google Vertex AI, NVIDIA NIM, AWS Bedrock, Novita AI, and the Vercel AI Gateway.
FAQ
What is the context window for Qwen3-Coder-480B-A35B-Instruct on AWS Bedrock?
Qwen3-Coder-480B-A35B-Instruct supports a 262k token context window on AWS Bedrock.
How does AWS Bedrock compare to other Qwen3-Coder-480B-A35B-Instruct providers?
Qwen3-Coder-480B-A35B-Instruct is available from 6 providers. The cheapest input pricing is $0.22/1M tokens from GCP Vertex AI.
Who created Qwen3-Coder-480B-A35B-Instruct?
Qwen3-Coder-480B-A35B-Instruct was created by Alibaba as part of the Qwen3-Coder model family.
Is Qwen3-Coder-480B-A35B-Instruct open source?
Qwen3-Coder-480B-A35B-Instruct is open source under Apache 2.0 according to the seed data.