Qwen3.5-VL¶
Class: Qwen35VLBlockV1
Source: inference.core.workflows.core_steps.models.foundation.qwen3_5vl.v1.Qwen35VLBlockV1
This workflow block runs Qwen3.5-VL—a vision language model that accepts an image and an optional text prompt—and returns a text answer based on a conversation template.
Type identifier¶
Use the following identifier in step "type" field: roboflow_core/qwen3_5vl@v1to add the block as
as step in your workflow.
Properties¶
| Name | Type | Description | Refs |
|---|---|---|---|
name |
str |
Enter a unique identifier for this step.. | ❌ |
prompt |
str |
Optional text prompt to provide additional context to Qwen3.5-VL. Otherwise it will just be a default one, which may affect the desired model behavior.. | ❌ |
model_version |
str |
The Qwen3.5-VL model to be used for inference.. | ✅ |
system_prompt |
str |
Optional system prompt to provide additional context to Qwen3.5-VL.. | ❌ |
enable_thinking |
bool |
If true, enables Qwen3.5-VL's thinking mode, which allows the model to generate reasoning tokens before answering. The thinking output will be returned in the 'thinking' field.. | ❌ |
max_new_tokens |
int |
Maximum number of tokens to generate. If not set, the model's default will be used. Consider increasing for thinking mode.. | ❌ |
The Refs column marks possibility to parametrise the property with dynamic values available
in workflow runtime. See Bindings for more info.
Available Connections¶
Compatible Blocks
Check what blocks you can connect to Qwen3.5-VL in version v1.
- inputs:
Stitch Images,Image Threshold,Stability AI Inpainting,Corner Visualization,Image Blur,Ellipse Visualization,Perspective Correction,Depth Estimation,Camera Calibration,Absolute Static Crop,Multi-Label Classification Model,Stability AI Image Generation,Grid Visualization,Background Color Visualization,Dynamic Crop,Image Slicer,Image Preprocessing,Relative Static Crop,Contrast Equalization,Background Subtraction,Morphological Transformation,Line Counter Visualization,SIFT,SIFT Comparison,Trace Visualization,Keypoint Visualization,Halo Visualization,Dot Visualization,Keypoint Detection Model,Pixelate Visualization,Single-Label Classification Model,Circle Visualization,Image Convert Grayscale,Icon Visualization,QR Code Generator,Semantic Segmentation Model,Halo Visualization,Camera Focus,Polygon Visualization,Color Visualization,Text Display,Reference Path Visualization,Object Detection Model,Instance Segmentation Model,Crop Visualization,Mask Visualization,Heatmap Visualization,Triangle Visualization,Blur Visualization,Bounding Box Visualization,Label Visualization,Classification Label Visualization,Camera Focus,Polygon Visualization,Image Slicer,Image Contours,Model Comparison Visualization,Stability AI Outpainting,Polygon Zone Visualization - outputs:
Image Threshold,Email Notification,Corner Visualization,Image Blur,Ellipse Visualization,OpenAI,Roboflow Dataset Upload,Time in Zone,Stitch OCR Detections,Depth Estimation,CogVLM,Google Gemini,Stability AI Image Generation,Time in Zone,Dynamic Crop,Instance Segmentation Model,Image Preprocessing,Morphological Transformation,Line Counter Visualization,Trace Visualization,LMM For Classification,Halo Visualization,Dot Visualization,GLM-OCR,Model Monitoring Inference Aggregator,Cache Get,Roboflow Custom Metadata,Pixel Color Count,Circle Visualization,Icon Visualization,QR Code Generator,S3 Sink,Detections Classes Replacement,Twilio SMS Notification,Halo Visualization,Anthropic Claude,SAM 3,Detections Consensus,Polygon Visualization,Text Display,Reference Path Visualization,Instance Segmentation Model,Llama 3.2 Vision,Roboflow Dataset Upload,Crop Visualization,Mask Visualization,CLIP Embedding Model,Heatmap Visualization,Webhook Sink,Cache Set,Google Vision OCR,Label Visualization,Classification Label Visualization,Florence-2 Model,Segment Anything 2 Model,Florence-2 Model,Polygon Zone Visualization,Stability AI Inpainting,Google Gemini,SAM 3,Perspective Correction,Anthropic Claude,OpenAI,Distance Measurement,OpenAI,PTZ Tracking (ONVIF),Background Color Visualization,Anthropic Claude,Size Measurement,Email Notification,SIFT Comparison,Contrast Equalization,Keypoint Visualization,Time in Zone,Line Counter,Path Deviation,Stitch OCR Detections,LMM,Perception Encoder Embedding Model,Line Counter,SAM 3,Seg Preview,Color Visualization,OpenAI,Roboflow Vision Events,Local File Sink,Detections Stitch,Twilio SMS/MMS Notification,YOLO-World Model,Triangle Visualization,Clip Comparison,Bounding Box Visualization,Polygon Visualization,Google Gemini,Path Deviation,Moondream2,Model Comparison Visualization,Stability AI Outpainting,Slack Notification
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
Qwen3.5-VL in version v1 has.
Bindings
-
input
images(image): The image to infer on..model_version(roboflow_model_id): The Qwen3.5-VL model to be used for inference..
-
output
parsed_output(dictionary): Dictionary.thinking(string): String value.
Example JSON definition of step Qwen3.5-VL in version v1
{
"name": "<your_step_name_here>",
"type": "roboflow_core/qwen3_5vl@v1",
"images": "$inputs.image",
"prompt": "What is in this image?",
"model_version": "qwen3_5-0.8b",
"system_prompt": "You are a helpful assistant.",
"enable_thinking": "<block_does_not_provide_example>",
"max_new_tokens": "<block_does_not_provide_example>"
}