Qwen: Qwen3.5-35B-A3B
Analysis Summary
Qwen3.5 35B A3B is a benchmarked multimodal model with text, image, and video input, a 262K context window, tool use, and function calling. Its coding capability is useful for assisted development, while the low pricing supports broad deployment across content and automation pipelines. The modality is valuable for visual briefs, screenshots, and mixed-media documents.
Typical workloads include SEO drafts, extraction, classification, content transformation, and coding tasks with human oversight. Its general intelligence and agentic results are limited, so it should not be trusted with open-ended planning, difficult research, or autonomous multi-tool execution. Long-context support helps capacity, but does not remove the need for validation.
Use it as a low-cost multimodal workhorse for bounded tasks. Pair it with a stronger reasoning model when decisions, complex synthesis, or final client recommendations are involved.
Assessed August 23, 2026
Editorial notes
Qwen3.5 35B A3B offers low-cost multimodal processing, useful coding, a 262K context, and tool calling, but limited reasoning and agentic depth restrict complex workflows.
Rankings consider pricing, capabilities, benchmarks, and real-world applicability and are refreshed as new models launch. Feedback?
DFO Verdict
Qwen3.5 35B A3B offers low-cost multimodal processing, useful coding, a 262K context, and tool calling, but limited reasoning and agentic depth restrict complex workflows.
How Qwen: Qwen3.5-35B-A3B compares
Qwen: Qwen3.5-35B-A3B ranks #130 of 433 AI models we track for overall intelligence, #102 of 206 for coding, #117 of 188 for agentic tasks. Its 262K-token context window is larger than 72% of the models we list. At $0.25 per million input tokens it is cheaper than 52% 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 value. 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 | $0.25 | $0.000250 |
| Output | $1.25 | $0.001250 |
What would Qwen: Qwen3.5-35B-A3B cost your business?
Pick the job that looks most like yours, then fine-tune with the sliders. Estimates update live.
A website chatbot handling around 100 customer conversations a day, a few short messages each.
Full calculator with 748 models → Price Calculator
These numbers get smaller with the right architecture.
We route routine calls to cheap models and save Qwen: Qwen3.5-35B-A3B for the hard ones. Most clients cut their estimate by 60-80%.
Talk to our teamAbout Qwen: Qwen3.5-35B-A3B
The Qwen3.5 Series 35B-A3B is a native vision-language model designed with a hybrid architecture that integrates linear attention mechanisms and a sparse mixture-of-experts model, achieving higher inference efficiency. Its overall..
Frequently asked questions about Qwen: Qwen3.5-35B-A3B
How much does Qwen: Qwen3.5-35B-A3B cost?
Qwen: Qwen3.5-35B-A3B costs $0.25 per million input tokens and $1.25 per million output tokens.
What is the context window of Qwen: Qwen3.5-35B-A3B?
Qwen: Qwen3.5-35B-A3B has a context window of 262,144 tokens (262K).
Is Qwen: Qwen3.5-35B-A3B good for coding?
On our coding benchmark index, Qwen: Qwen3.5-35B-A3B ranks #102 of 206 models, placing it in the broader range of the field for code generation and debugging.
What can Qwen: Qwen3.5-35B-A3B do?
Qwen: Qwen3.5-35B-A3B supports image/vision input, tool use, and function calling.
Who created Qwen: Qwen3.5-35B-A3B?
Qwen: Qwen3.5-35B-A3B is developed by Qwen and was released on February 25, 2026.