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Qwen-VL

Class: QwenVlmBlockV1

Source: inference.core.workflows.core_steps.models.foundation.qwen_vlm.v1.QwenVlmBlockV1

Run any Qwen vision-language model — natively on Roboflow infrastructure or via OpenRouter.

You can specify arbitrary text prompts or predefined ones, the block supports the following types of prompt:

  • Open Prompt (unconstrained) - Use any prompt to generate a raw response

  • Text Recognition (OCR) (ocr) - Model recognizes text in the image

  • Visual Question Answering (visual-question-answering) - Model answers the question you submit in the prompt

  • Captioning (short) (caption) - Model provides a short description of the image

  • Captioning (detailed-caption) - Model provides a long description of the image

  • Single-Label Classification (classification) - Model classifies the image content as one of the provided classes

  • Multi-Label Classification (multi-label-classification) - Model classifies the image content as one or more of the provided classes

  • Unprompted Object Detection (object-detection) - Model detects and returns the bounding boxes for prominent objects in the image

  • Structured Output Generation (structured-answering) - Model returns a JSON response with the specified fields

🛠️ Backend selection

  • Native (Roboflow) — small Qwen-VL models (0.8B–7B) run on the same infrastructure as your other Roboflow models. Lower latency. Recommended for tasks like OCR, captioning, and visual question answering.

  • OpenRouter — large hosted Qwen models (9B–397B) reached via OpenRouter. Defaults to a Roboflow-managed API key and bills your Roboflow credits. Paste your own sk-or-... key in the api_key field to bypass Roboflow billing. Recommended for structured tasks that benefit from larger models (classification, object-detection, structured-answering).

The model_version dropdown lists every supported variant; each is bound to one backend. A validator catches mismatches between your selected backend and model.

🔒 Privacy filter (OpenRouter only)

  • No data collection (default) – providers may not train on your inputs.
  • Allow data collection – broader provider pool.
  • Zero data retention – strictest, restricts to providers that retain nothing.

Type identifier

Use the following identifier in step "type" field: roboflow_core/qwen_vlm@v1to add the block as as step in your workflow.

Properties

Name Type Description Refs
name str Enter a unique identifier for this step.. ❌
api_key str OpenRouter API key (only used when backend=openrouter). Defaults to Roboflow's managed key. Provide your own sk-or-... key to call OpenRouter directly without Roboflow billing.. ✅
privacy_level str Provider privacy filter (only used when backend=openrouter). Stricter levels reduce the pool of providers and may increase per-call cost on the managed key.. ❌
max_tokens int Maximum number of tokens the model can generate in its response.. ❌
temperature float Sampling temperature (only used when backend=openrouter). The native Qwen-VL runtime doesn't accept a temperature knob. Range 0.0-2.0 — higher = more random / "creative" generations.. ✅
max_concurrent_requests int Maximum number of OpenRouter requests to run in parallel for a batch of images (only used when backend=openrouter). The native backend processes images sequentially. If unset, falls back to the global Workflows Execution Engine default. Restrict this if you hit OpenRouter rate limits.. ❌
backend str Where to run inference. Native = Roboflow infrastructure. OpenRouter = large hosted Qwen models via OpenRouter.. ❌
model_version str Native Qwen-VL variant. Pick a pre-trained model or Fine-tuned model to use a Qwen3 fine-tune from your workspace.. ✅
fine_tuned_model_id str Fine-tuned Qwen3-VL model from your workspace, in workspace/version form.. ✅
openrouter_model_version str OpenRouter-hosted Qwen variant.. ✅
task_type str Task type to be performed by model. Value determines required parameters and output response.. ❌
prompt str Text prompt to the Qwen model. ✅
enable_thinking bool Enable Qwen3.5-VL's reasoning mode, where the model emits thinking tokens before its answer. The reasoning trace is returned in the thinking output. Only the Qwen 3.5 VL 2B checkpoint (and Qwen3-VL fine-tunes derived from it) supports this; ignored elsewhere.. ❌
output_structure Dict[str, str] Dictionary with structure of expected JSON response. ❌
classes List[str] List of classes to be used. ✅

The Refs column marks possibility to parametrise the property with dynamic values available in workflow runtime. See Bindings for more info.

Runtime compatibility

requires_internet — air-gapped / offline deployments
This block depends on a service that is not reachable from fully offline / air-gapped deployments.

Available Connections

Compatible Blocks

Check what blocks you can connect to Qwen-VL in version v1.

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds Qwen-VL in version v1 has.

Bindings

  • input

    • api_key (Union[string, ROBOFLOW_MANAGED_KEY, secret]): OpenRouter API key (only used when backend=openrouter). Defaults to Roboflow's managed key. Provide your own sk-or-... key to call OpenRouter directly without Roboflow billing..
    • temperature (float): Sampling temperature (only used when backend=openrouter). The native Qwen-VL runtime doesn't accept a temperature knob. Range 0.0-2.0 — higher = more random / "creative" generations..
    • images (image): The image to infer on..
    • model_version (string): Native Qwen-VL variant. Pick a pre-trained model or Fine-tuned model to use a Qwen3 fine-tune from your workspace..
    • fine_tuned_model_id (Union[roboflow_model_id, string]): Fine-tuned Qwen3-VL model from your workspace, in workspace/version form..
    • openrouter_model_version (string): OpenRouter-hosted Qwen variant..
    • prompt (string): Text prompt to the Qwen model.
    • classes (list_of_values): List of classes to be used.

  • output

Example JSON definition of step Qwen-VL in version v1 
{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/qwen_vlm@v1",
    "api_key": "rf_key:account",
    "privacy_level": "<block_does_not_provide_example>",
    "max_tokens": "<block_does_not_provide_example>",
    "temperature": "<block_does_not_provide_example>",
    "max_concurrent_requests": "<block_does_not_provide_example>",
    "images": "$inputs.image",
    "backend": "<block_does_not_provide_example>",
    "model_version": "Qwen 3.5 VL 2B",
    "fine_tuned_model_id": "your-workspace/3",
    "openrouter_model_version": "Qwen 3.6 27B",
    "task_type": "<block_does_not_provide_example>",
    "prompt": "my prompt",
    "enable_thinking": "<block_does_not_provide_example>",
    "output_structure": {
        "my_key": "description"
    },
    "classes": [
        "class-a",
        "class-b"
    ]
}