Qwen3-Coder 480B-A35B Instruct
Qwen3-Coder 480B-A35B Instruct is a language model from Qwen released on Apr 1, 2025. It reads text and writes text, with a 262K token context window and up to 66K tokens per reply.
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It costs $1.50 per million input tokens and $7.50 per million output tokens.
It supports tool calling and structured JSON output, and its weights are open, so you can host it yourself.
15 providers serve it, including SiliconFlow, Amazon Bedrock and Hugging Face. The lowest input price is $0.20 per million tokens at submodel.
- Modalities
- In / out price
- $1.50 / $7.50 per 1M
- Context
- 262K
- Max output
- 66K
- Released
- Apr 1, 2025
- Knowledge cutoff
- Apr 2025
- Tool calling
- Structured output
- Reasoning
- Prompt caching
- Open weights
- Free to use
Qwen3-Coder 480B-A35B Instruct pricing
USD, as listed on Oct 15, 2026. Most bills are input heavy, so the cached input rate matters as much as the headline price.
| Input | $1.50 / 1M tokens | |
|---|---|---|
| Output | $7.50 / 1M tokens | |
| Prompts over 32K | $2.70 in, $13.50 out | long context rate |
| Prompts over 128K | $4.50 in, $22.50 out | long context rate |
Qwen3-Coder 480B-A35B Instruct providers
15 providers serve it, including SiliconFlow, Amazon Bedrock and Hugging Face. The lowest input price is $0.20 per million tokens at submodel. Each host sets its own price and limits, so the cheapest one is not always the one with the longest context.
| Provider | Input /M | Output /M | Cache read /M | Context | Max output |
|---|---|---|---|---|---|
| Alibaba First party | $1.50 | $7.50 | – | 262K | 66K |
| SiliconFlow | $0.25 | $1 | – | 262K | 262K |
| Amazon Bedrock | $0.45 | $1.80 | – | 131K | 66K |
| Hugging Face | $2 | $2 | – | 262K | 67K |
| submodel | $0.20 | $0.80 | – | 262K | 262K |
| Merge Gateway | $0.22 | $1.80 | – | 131K | 33K |
| SiliconFlow (China) | $0.25 | $1 | – | 262K | 262K |
| Abacus | $0.29 | $1.20 | – | 262K | 16K |
| Jiekou.AI | $0.29 | $1.20 | – | 262K | 66K |
| DevPass (LLM Gateway) | $0.38 | $1.55 | – | 262K | 66K |
| LLM Gateway | $0.38 | $1.55 | – | 262K | 66K |
| Eden AI | $0.40 | $1.60 | – | 262K | 66K |
Showing 12 of 15 providers: the lab first, then the major clouds, then the cheapest resellers.
What Qwen3-Coder 480B-A35B Instruct costs per month
Pick a workload close to yours or type your own volumes.
Supported request parameters
What you can set when you call Qwen3-Coder 480B-A35B Instruct through an OpenAI compatible API.
- Tools
tools - Structured outputs
structured_outputs - Temperature
temperature
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Qwen3-Coder 480B-A35B Instruct questions
How much does the Qwen3-Coder 480B-A35B Instruct API cost?
$1.50 per million input tokens and $7.50 per million output tokens. Prompts over 32K tokens bill at $2.70 input and $13.50 output. The estimator on this page turns that into a monthly bill for your own workload.
What is the context window of Qwen3-Coder 480B-A35B Instruct?
262,144 tokens of input, and it can write up to 65,536 tokens in one reply. As a rough guide, a million tokens is around 750,000 English words.
Which providers serve Qwen3-Coder 480B-A35B Instruct?
15 providers serve it, including SiliconFlow, Amazon Bedrock and Hugging Face. The lowest input price is $0.20 per million tokens at submodel. Prices differ by host, so the Providers table on this page lists each one with its input and output price.
Does Qwen3-Coder 480B-A35B Instruct support tool calling?
Yes. It accepts tool definitions and can return JSON that matches a schema, which is what an agent needs to call your APIs.
Is Qwen3-Coder 480B-A35B Instruct open source?
Its weights are published, so you can run it on your own hardware or a cloud of your choice. Read the license before commercial use.
When was Qwen3-Coder 480B-A35B Instruct released?
Apr 1, 2025, with training data up to Apr 2025.
Catalog data from models.dev (MIT licensed), refreshed daily, last on Oct 15, 2026. The summary is written from these facts.
Building on Qwen3-Coder 480B-A35B Instruct?
I test your real tasks on it and the two closest alternatives, then ship the agent on whichever wins on cost and accuracy.
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