Qwen: Qwen3.5 397B A17B
Analysis Summary
Qwen3.5 397B A17B is a large multimodal model with a strong coding result and useful support for agent workflows. It handles text, images, and video, offers a 262K context window, and includes tool use and function calling. That profile gives it practical reach across software tasks, document interpretation, and connected business automation.
It suits code generation, repository assistance, technical content, multimodal review, and tool-driven internal agents. Coding capability is a clear strength, while the lower general intelligence and agentic results indicate that complex planning, ambiguous strategy, and long autonomous sequences need evaluation and safeguards. For client-facing prose, editorial review remains advisable for tone and factual consistency.
Pricing is competitive for a model with this breadth, making it suitable for recurring workloads. Use it as a flexible value choice when coding and multimodality matter more than frontier reasoning.
Assessed August 9, 2026
Editorial notes
Qwen3.5 397B A17B combines strong coding, multimodal input, a 262K context, tool use, and competitive pricing, making it a flexible engineering and automation option with moderate reasoning depth.
Rankings consider pricing, capabilities, benchmarks, and real-world applicability and are refreshed as new models launch. Feedback?
DFO Verdict
Qwen3.5 397B A17B combines strong coding, multimodal input, a 262K context, tool use, and competitive pricing, making it a flexible engineering and automation option with moderate reasoning depth.
How Qwen: Qwen3.5 397B A17B compares
Qwen: Qwen3.5 397B A17B ranks #97 of 425 AI models we track for overall intelligence, #69 of 198 for coding, #87 of 180 for agentic tasks. Its 262K-token context window is larger than 73% of the models we list. At $0.39 per million input tokens it is cheaper than 43% of comparable models.
Dark bar = input · light bar = output, scaled to the priciest peer.
1M tokens ≈ 8 full-length novels or ~2,500 pages of business documents in a single request.
Strongest on business fit. The pulled-in technical corner is the trade-off, and if the shape matters more than the price, this is your model.
Compare shapes side-by-side →Pricing
| Token Type | Cost per 1M tokens | Cost per 1K tokens |
|---|---|---|
| Input | $0.39 | $0.000390 |
| Output | $2.34 | $0.002340 |
What would Qwen: Qwen3.5 397B A17B cost your business?
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A website chatbot handling around 100 customer conversations a day, a few short messages each.
Full calculator with 701 models → Price Calculator
These numbers get smaller with the right architecture.
We route routine calls to cheap models and save Qwen: Qwen3.5 397B A17B for the hard ones. Most clients cut their estimate by 60-80%.
Talk to our teamAbout Qwen: Qwen3.5 397B A17B
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..
Frequently asked questions about Qwen: Qwen3.5 397B A17B
How much does Qwen: Qwen3.5 397B A17B cost?
Qwen: Qwen3.5 397B A17B costs $0.39 per million input tokens and $2.34 per million output tokens.
What is the context window of Qwen: Qwen3.5 397B A17B?
Qwen: Qwen3.5 397B A17B has a context window of 262,144 tokens (262K).
Is Qwen: Qwen3.5 397B A17B good for coding?
On our coding benchmark index, Qwen: Qwen3.5 397B A17B ranks #69 of 198 models, placing it in the broader range of the field for code generation and debugging.
What can Qwen: Qwen3.5 397B A17B do?
Qwen: Qwen3.5 397B A17B supports image/vision input, tool use, and function calling.
Who created Qwen: Qwen3.5 397B A17B?
Qwen: Qwen3.5 397B A17B is developed by Qwen and was released on February 16, 2026.