Qwen3.5 4B (Reasoning)
Analysis Summary
Qwen3.5 4B Reasoning is a small reasoning model positioned for inexpensive, high-volume inference. It has measurable coding, instruction-following, long-context, and tool-oriented results, but each capability is constrained by its limited general reasoning level. No vision, tool-use, or function-calling capability is provided in the supplied data.
It is best suited to routine SEO transformations, metadata generation, simple classification, short-form drafting, and first-pass content operations. It should not be the default for complex research, autonomous coding, nuanced brand writing, or decisions requiring sustained reasoning. The very low input and output prices make it useful as a routing target for repetitive workloads.
Deploy it for low-risk automation with validation, while escalating strategic content and complex technical tasks to a stronger model.
Assessed September 7, 2026
Editorial notes
Qwen3.5 4B Reasoning offers very low-cost inference and useful structured reasoning for lightweight classification, SEO, and routine content tasks. Its small model size limits coding depth, long-context reliability, and complex client-facing analysis.
Rankings consider pricing, capabilities, benchmarks, and real-world applicability and are refreshed as new models launch. Feedback?
DFO Verdict
Qwen3.5 4B Reasoning offers very low-cost inference and useful structured reasoning for lightweight classification, SEO, and routine content tasks. Its small model size limits coding depth, long-context reliability, and complex client-facing analysis.
Benchmark scores
Magenta = intelligence · Ink = technical/agentic · Cyan = content & long-context · Grey = community benchmarks. Data: Artificial Analysis, Hugging Face.
13.1 Intelligence Index·22.6 Coding Index
How Qwen3.5 4B (Reasoning) compares
Qwen3.5 4B (Reasoning) ranks #193 of 438 AI models we track for overall intelligence, #140 of 210 for coding. At $0.03 per million input tokens it is cheaper than 79% 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 | $0.03 | $0.000030 |
| Output | $0.15 | $0.000150 |
What would Qwen3.5 4B (Reasoning) 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 779 models → Price Calculator
These numbers get smaller with the right architecture.
We route routine calls to cheap models and save Qwen3.5 4B (Reasoning) for the hard ones. Most clients cut their estimate by 60-80%.
Talk to our teamFrequently asked questions about Qwen3.5 4B (Reasoning)
How much does Qwen3.5 4B (Reasoning) cost?
Qwen3.5 4B (Reasoning) costs $0.03 per million input tokens and $0.15 per million output tokens.
Is Qwen3.5 4B (Reasoning) good for coding?
On our coding benchmark index, Qwen3.5 4B (Reasoning) ranks #140 of 210 models, placing it in the broader range of the field for code generation and debugging.
Who created Qwen3.5 4B (Reasoning)?
Qwen3.5 4B (Reasoning) is developed by Alibaba and was released on March 2, 2026.