Qwen3.5-Flash

Qwen3.5-Flash by Alibaba excels in the Coding category, where it ranks #167 with a composite score of 69/100. The Qwen3.5 native vision-language Flash models are built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. Compared to the... It is particularly strong in areas highlighted by its top benchmark performance and adoption metrics, making it suitable for both individual developers and enterprise teams looking for a reliable coding solution.

Qwen3.5-Flash is priced at $0.07 per million input tokens and $0.26 per million output tokens (USD). Contact the provider for volume discounts and enterprise pricing. Pricing is competitive within the coding category and reflects the model's quality-to-cost ratio.

In the Coding category, Qwen3.5-Flash holds rank #167 out of 377 models tracked. Its quality rank is #167 and adoption rank is #167. You can use our comparison tool at /compare to see detailed side-by-side metrics with specific alternatives. Key differentiators include its composite scoring across benchmarks, community sentiment, and real-world adoption rates.

Qwen3.5-Flash has been evaluated across 6 different signals. Its strongest areas include Capabilities (83/100), Benchmarks (66/100), Pricing (100/100). These scores are derived from industry-standard benchmarks, community ratings, and real-world performance metrics. The composite score of 69/100 reflects a weighted combination of all tracked signals.

Qwen3.5-Flash is a paid model, though some providers may offer trial credits or limited free tiers for evaluation. Check Alibaba's website for current free tier availability and promotional offers.

Qwen3.5-Flash supports a 1,000K token context window (1,000,000 tokens total). That translates to roughly 750,000 words in a single prompt. This is large enough to process entire codebases, research papers, or long conversation histories in one shot.

Qwen3.5-Flash can generate up to 66K output tokens (65,536 tokens) per response. That is roughly 49,152 words. This is enough for generating complete code files, detailed reports, or long-form content in a single response.

Qwen3.5-Flash supports image understanding (vision), function/tool calling, structured JSON output, extended reasoning/chain-of-thought, streaming responses. Function calling lets you integrate it with external APIs and tools programmatically. Vision support means it can analyze images, screenshots, and diagrams alongside text. These capabilities determine which workflows and integrations the model can handle natively.

Qwen3.5-Flash was developed by Alibaba. It was released on February 25, 2026. You can access it through Alibaba's API. Check our provider page for all models from Alibaba and how they compare against each other.

Pick Qwen3.5-Flash when you need a solid balance of cost and capability for everyday development tasks, content generation, and standard API integrations. If your task is straightforward text completion or classification, a cheaper model might give you 90% of the quality at a fraction of the price. Run a quick benchmark on your actual use case before committing.

You can access Qwen3.5-Flash through Alibaba's API using standard HTTP requests or their official SDK. Most providers support OpenAI-compatible endpoints, so switching between models often requires changing just the model name in your API call. Streaming is supported for real-time token-by-token output. For production use, implement proper error handling, rate limiting, and cost monitoring.