Qwen3.5¶
Class: Qwen35VLBlockV2
Source: inference.core.workflows.core_steps.models.foundation.qwen3_5vl.v2.Qwen35VLBlockV2
This workflow block runs Qwen3.5—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@v2to 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. Otherwise it will just be a default one, which may affect the desired model behavior.. | ❌ |
model_version |
str |
The Qwen3.5 model to be used for inference.. | ✅ |
system_prompt |
str |
Optional system prompt to provide additional context to Qwen3.5.. | ❌ |
max_new_tokens |
int |
Maximum number of tokens to generate. If not set, the model's default will be used.. | ❌ |
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 in version v2.
- inputs:
Triangle Visualization,Background Color Visualization,Keypoint Detection Model,Heatmap Visualization,Classification Label Visualization,Contrast Equalization,Image Contours,Text Display,Icon Visualization,Pixelate Visualization,Circle Visualization,Mask Visualization,Polygon Zone Visualization,Ellipse Visualization,SIFT,Stitch Images,Image Slicer,Reference Path Visualization,Camera Focus,Object Detection Model,Image Slicer,Absolute Static Crop,Image Blur,Polygon Visualization,Polygon Visualization,Single-Label Classification Model,Keypoint Detection Model,Background Subtraction,Image Threshold,Halo Visualization,Line Counter Visualization,Stability AI Inpainting,Camera Focus,Morphological Transformation,QR Code Generator,Stability AI Outpainting,Grid Visualization,Image Preprocessing,Dynamic Crop,Color Visualization,Blur Visualization,Multi-Label Classification Model,Corner Visualization,Object Detection Model,Label Visualization,Stability AI Image Generation,Keypoint Visualization,Contrast Enhancement,Single-Label Classification Model,Dot Visualization,Camera Calibration,Morphological Transformation,Semantic Segmentation Model,Trace Visualization,Model Comparison Visualization,Crop Visualization,Instance Segmentation Model,Image Convert Grayscale,Relative Static Crop,SIFT Comparison,Depth Estimation,Semantic Segmentation Model,Perspective Correction,Halo Visualization,Instance Segmentation Model,Multi-Label Classification Model,Bounding Box Visualization - outputs:
Per-Class Confidence Filter,SAM 3,Detections Consensus
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
Qwen3.5 in version v2 has.
Bindings
-
input
images(image): The image to infer on..model_version(roboflow_model_id): The Qwen3.5 model to be used for inference..
-
output
parsed_output(dictionary): Dictionary.
Example JSON definition of step Qwen3.5 in version v2
{
"name": "<your_step_name_here>",
"type": "roboflow_core/qwen3_5vl@v2",
"images": "$inputs.image",
"prompt": "What is in this image?",
"model_version": "qwen3_5-0.8b",
"system_prompt": "You are a helpful assistant.",
"max_new_tokens": "<block_does_not_provide_example>"
}