Official model documentation
Fields: model identity
The Qwen3.5 native vision-language series Plus models are built on a hybrid architecture that integrates linear attention mechanisms with sparse mixture-of-experts models, achieving higher inference efficiency. In a variety of…
- Context
- 1M
- Max output
- 66K
- Input
- $0.26
- Output
- $1.56
Recommended use cases
Strengths in this dataset
- 1,000,000-token context window
- text, image, video input
- 16 supported API parameters listed
Limits and caveats
- Provider behavior and pricing can change; verify the linked sources before production use.
Capability
Model-native facts
Model- Reasoning
- Supported
- Open weights
- Unknown
Provider endpoint facts
Provider endpoint- Tool calling
- Supported
- Structured output
- Supported
- Streaming
- Unknown
- Prompt cache
- Unknown
- Batch
- Unknown
- Fine-tuning
- Unknown
Qwen3.5 Plus 2026-02-15 Provider pricing
Provider endpoint: qwen/qwen3.5-plus-02-15
- Input
- $0.26 per 1M tokens
- Output
- $1.56 per 1M tokens
- Cached input
- Unknown per 1M tokens
- Image output
- Unknown per 1M tokens
Sources and verification
OpenRouter Models API
Fields: identity, description, modalities, context window, maximum output, pricing, supported parameters
Frequently asked questions
Answers are generated from the same sourced model and provider facts shown above.
The Qwen3.5 native vision-language series Plus models are built on a hybrid architecture that integrates linear attention mechanisms with sparse mixture-of-experts models, achieving higher inference efficiency. In a variety of…
Model specifications and prices may vary by provider and change over time. AIToolly displays sources and verification dates so users can confirm critical details before production use.