Qwen3.5 397B A17B
qwen/
The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency.
$0.66 in · $3.96 out per 1M tokens262k contextFeb 16, 2026
A typical message: about 500 tokens you send and 500 it writes.
Spec sheet
Published facts from the catalog, billed prices and what we measured here. Anything not measured says so.
Price, billed here
- Input, per 1M tokens
- $0.66provider $0.60
- Output, per 1M tokens
- $3.96provider $3.60
- Cached input, per 1M
- $0.132provider $0.12
- Margin
- +10%
Context and formats
- Context window
- 262,144 tokens
- Longest answer
- 64,000 tokens
- Reads
- text, images, and video
- Makes
- text
- First listed
- 2026-02-16
Measured here, last 7 days
- First token, median
- not measured
- Answered without error
- not measured
Tools and JSON
- Tool calling
- declaredthe provider's claim, not yet measured here
- JSON output
- declaredthe provider's claim, not yet measured here
Price and latency history as JSON: GET /.
About
The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. It delivers...
In Qwen's words.
Try it here
Measured here
Call it
Use one OpenAI compatible endpoint, this model's id and an am_live_ key from the dashboard. You can also try it in chat first with no key.
curl https://useantimatter.com/v1/chat/completions \
-H "Authorization: Bearer $ANTIMATTER_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model": "qwen/qwen3.5-397b-a17b", "messages": [{"role": "user", "content": "Hello"}]}'Everything else is in the docs.
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<a href="https://useantimatter.com/planet/qwen/qwen3.5-397b-a17b"><img src="https://useantimatter.com/api/badge/price?id=qwen%2Fqwen3.5-397b-a17b" alt="Qwen3.5 397B A17B price on Antimatter" height="28"></a>More from Qwen
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