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 3 series, these models deliver a leap forward in performance for both pure text and multimodal tasks, offering fast response times while balancing inference speed and overall performance.
Modalities
In / Out Price
$0.065 / $0.26per 1M
Context
1M
Released
Feb 25, 2026
This model is hosted by one provider. OpenRouter forwards every request to it directly — no routing decisions to make.
The average price customers actually pay for this model, next to the prices providers post. Caching and discounts mean the price actually paid is often well below the listed one.
Throughput is how fast the model writes (tokens per second — higher is better). Latency is total round-trip time (lower is better). TTFT is time-to-first-token — how long before you see anything appear (lower is better).
Uptime is the percentage of the past 3 days that at least one provider was responding to requests. Availability is the percentage of time that inference was successfully served. OpenRouter continuously monitors and uses the next-best provider when one returns an error.
Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for.
Token volume and request traffic to this model over time.
Drop-in code to call this model. OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. The only thing that changes between models is the model slug below.
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.
Qwen3.5-Flash costs $0.065/M input tokens and $0.26/M output tokens.
Qwen3.5-Flash has a 1,000,000 token context window. It supports up to 65,536 completion tokens.
Yes. Qwen3.5-Flash accepts tools and tool_choice for function calling. It also supports structured outputs via a JSON schema in response_format.
Qwen3.5-Flash accepts text, images and video as input and returns text.
Qwen3.8 27B, Qwen3.8 2.4T A95B, Qwen3.8 Max and 46 more are other text models from Qwen.
Qwen3.5-Flash was released on February 25, 2026.
| $0.065 | $0.26 | 0.58s | 40 tps |
Throughput
40tok/s
P50, best across providers
Latency
0.58s
P50, best provider
100.00%
99.12%
When an error occurs in an upstream provider, we can recover by routing to another healthy provider, if your request filters allow it. You can access per-provider uptime data programmatically through the Endpoints API. Learn more about our load balancing and customization options.
