> For the complete documentation index, see [llms.txt](https://docs.roboflow.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.roboflow.com/workflows/blocks/blocks/run-a-model/llama3-2-vision.md).

# Llama 3.2 Vision

Run Llama 3.2 Vision via OpenRouter.

## v2

Ask a question to Llama 3.2 Vision model.

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

#### 🛠️ API providers and model variants

Llama 3.2 Vision is exposed via [OpenRouter](https://openrouter.ai/). By default this block uses the **Roboflow-managed OpenRouter key** and bills your Roboflow credits - no extra setup needed. To bypass Roboflow billing, paste your own `sk-or-...` key into the `api_key` field.

The `privacy_level` field controls which OpenRouter providers may serve the request:

* **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.

#### 💡 Further reading and Acceptable Use Policy

{% hint style="warning" %}
**Model license**

Check the [Llama 3.2 license](https://www.llama.com/llama3_2/license/) before use.
{% endhint %}

### Type identifier

Use the following identifier in step `"type"` field: `roboflow_core/llama_vision@v2` to add the block as a step in your workflow.

### Properties

| **Name**                  | **Type**         | **Description**                                                                                                                                                                  | Refs |
| ------------------------- | ---------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---- |
| `name`                    | `str`            | Enter a unique identifier for this step..                                                                                                                                        | ❌    |
| `api_key`                 | `str`            | OpenRouter API key. Defaults to Roboflow's managed key, billed in credits via Roboflow. Provide your own `sk-or-...` key to call OpenRouter directly without Roboflow billing..  | ✅    |
| `privacy_level`           | `str`            | Provider privacy filter. 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`          | Temperature to sample from the model - value in range 0.0-2.0, the higher - the more random / "creative" the generations are..                                                   | ✅    |
| `max_concurrent_requests` | `int`            | Number of concurrent requests for batches of images. If not given - block defaults to value configured globally in Workflows Execution Engine. Restrict if you hit rate limits.. | ❌    |
| `task_type`               | `str`            | Task type to be performed by model. Value determines required parameters and output response..                                                                                   | ❌    |
| `prompt`                  | `str`            | Text prompt to the Llama model.                                                                                                                                                  | ✅    |
| `output_structure`        | `Dict[str, str]` | Dictionary with structure of expected JSON response.                                                                                                                             | ❌    |
| `classes`                 | `List[str]`      | List of classes to be used.                                                                                                                                                      | ✅    |
| `model_version`           | `str`            | Model 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.

### Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds `Llama 3.2 Vision` in version `v2` has.

<details>

<summary>Input and output bindings</summary>

* input
  * `api_key` (*Union\[*[*`ROBOFLOW_MANAGED_KEY`*](/workflows/developer-guide/developer-guide/kinds/roboflow-managed-key.md)*,* [*`secret`*](/workflows/developer-guide/developer-guide/kinds/secret.md)*,* [*`string`*](/workflows/developer-guide/developer-guide/kinds/string.md)*]*): OpenRouter API key. Defaults to Roboflow's managed key, billed in credits via Roboflow. Provide your own `sk-or-...` key to call OpenRouter directly without Roboflow billing..
  * `temperature` ([*`float`*](/workflows/developer-guide/developer-guide/kinds/float.md)): Temperature to sample from the model - value in range 0.0-2.0, the higher - the more random / "creative" the generations are..
  * `images` ([*`image`*](/workflows/developer-guide/developer-guide/kinds/image.md)): The image to infer on..
  * `prompt` ([*`string`*](/workflows/developer-guide/developer-guide/kinds/string.md)): Text prompt to the Llama model.
  * `classes` ([*`list_of_values`*](/workflows/developer-guide/developer-guide/kinds/list-of-values.md)): List of classes to be used.
  * `model_version` ([*`string`*](/workflows/developer-guide/developer-guide/kinds/string.md)): Model to be used.
* output
  * `output` (*Union\[*[*`string`*](/workflows/developer-guide/developer-guide/kinds/string.md)*,* [*`language_model_output`*](/workflows/developer-guide/developer-guide/kinds/language-model-output.md)*]*): String value if `string` or LLM / VLM output if `language_model_output`.
  * `classes` ([`list_of_values`](/workflows/developer-guide/developer-guide/kinds/list-of-values.md)): List of values of any type.

</details>

<details>

<summary>Example JSON definition</summary>

```json
{
	    "name": "<your_step_name_here>",
	    "type": "roboflow_core/llama_vision@v2",
	    "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",
	    "task_type": "<block_does_not_provide_example>",
	    "prompt": "my prompt",
	    "output_structure": {
	        "my_key": "description"
	    },
	    "classes": [
	        "class-a",
	        "class-b"
	    ],
	    "model_version": "11B - OpenRouter"
	}
```

</details>

## v1

Ask a question to Llama 3.2 Vision model with vision capabilities.

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

{% hint style="warning" %}
**Issues with structured prompting**

Model tends to be quite unpredictable when structured output (in our case JSON document) is expected. That problems may impact tasks like `structured-answering`, `classification` or `multi-label-classification`.

The cause seems to be quite sensitive "filters" of inappropriate content embedded in model.
{% endhint %}

#### 🛠️ API providers and model variants

Llama Vision 3.2 model is exposed via [OpenRouter API](https://openrouter.ai/) and we require passing [OpenRouter API Key](https://openrouter.ai/docs/api-keys) to run.

There are different versions of the model supported:

* smaller version (`11B`) is faster and cheaper, yet you can expect better quality of results using `90B` version
* `Regular` version is paid (and usually faster) API, whereas `Free` is free for use for OpenRouter clients (state at 01.01.2025)

As for now, OpenRouter is the only provider for Llama 3.2 Vision model, but we will keep you posted if the state of the matter changes.

{% hint style="warning" %}
**API Usage Charges**

OpenRouter is external third party providing access to the model and incurring charges on the usage. Please check out pricing before use:

* [Llama 3.2 Vision 11B (Regular)](https://openrouter.ai/meta-llama/llama-3.2-11b-vision-instruct/providers)
* [Llama 3.2 Vision 90B (Regular)](https://openrouter.ai/meta-llama/llama-3.2-90b-vision-instruct/providers)
  {% endhint %}

#### 💡 Further reading and Acceptable Use Policy

{% hint style="warning" %}
**Model license**

Check out [model license](https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/LICENSE) before use.
{% endhint %}

[Click here](https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/MODEL_CARD_VISION.md) for the original model card.

Usage of this model is subject to Meta's [Acceptable Use Policy](https://www.llama.com/llama3/use-policy/).

### Type identifier

Use the following identifier in step `"type"` field: `roboflow_core/llama_3_2_vision@v1` to add the block as a step in your workflow.

### Properties

| **Name**                  | **Type**         | **Description**                                                                                                                                                                                                                | Refs |
| ------------------------- | ---------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | ---- |
| `name`                    | `str`            | Enter a unique identifier for this step..                                                                                                                                                                                      | ❌    |
| `task_type`               | `str`            | Task type to be performed by model. Value determines required parameters and output response..                                                                                                                                 | ❌    |
| `prompt`                  | `str`            | Text prompt to the Llama model.                                                                                                                                                                                                | ✅    |
| `output_structure`        | `Dict[str, str]` | Dictionary with structure of expected JSON response.                                                                                                                                                                           | ❌    |
| `classes`                 | `List[str]`      | List of classes to be used.                                                                                                                                                                                                    | ✅    |
| `api_key`                 | `str`            | Your Llama Vision API key (dependent on provider, ex: OpenRouter API key).                                                                                                                                                     | ✅    |
| `model_version`           | `str`            | Model to be used.                                                                                                                                                                                                              | ✅    |
| `max_tokens`              | `int`            | Maximum number of tokens the model can generate in it's response..                                                                                                                                                             | ❌    |
| `temperature`             | `float`          | Temperature to sample from the model - value in range 0.0-2.0, the higher - the more random / "creative" the generations are..                                                                                                 | ✅    |
| `max_concurrent_requests` | `int`            | Number of concurrent requests that can be executed by block when batch of input images provided. If not given - block defaults to value configured globally in Workflows Execution Engine. Please restrict if you hit limits.. | ❌    |

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.

### Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds `Llama 3.2 Vision` in version `v1` has.

<details>

<summary>Input and output bindings</summary>

* input
  * `images` ([*`image`*](/workflows/developer-guide/developer-guide/kinds/image.md)): The image to infer on..
  * `prompt` ([*`string`*](/workflows/developer-guide/developer-guide/kinds/string.md)): Text prompt to the Llama model.
  * `classes` ([*`list_of_values`*](/workflows/developer-guide/developer-guide/kinds/list-of-values.md)): List of classes to be used.
  * `api_key` ([*`string`*](/workflows/developer-guide/developer-guide/kinds/string.md)): Your Llama Vision API key (dependent on provider, ex: OpenRouter API key).
  * `model_version` ([*`string`*](/workflows/developer-guide/developer-guide/kinds/string.md)): Model to be used.
  * `temperature` ([*`float`*](/workflows/developer-guide/developer-guide/kinds/float.md)): Temperature to sample from the model - value in range 0.0-2.0, the higher - the more random / "creative" the generations are..
* output
  * `output` (*Union\[*[*`string`*](/workflows/developer-guide/developer-guide/kinds/string.md)*,* [*`language_model_output`*](/workflows/developer-guide/developer-guide/kinds/language-model-output.md)*]*): String value if `string` or LLM / VLM output if `language_model_output`.
  * `classes` ([`list_of_values`](/workflows/developer-guide/developer-guide/kinds/list-of-values.md)): List of values of any type.

</details>

<details>

<summary>Example JSON definition</summary>

```json
{
	    "name": "<your_step_name_here>",
	    "type": "roboflow_core/llama_3_2_vision@v1",
	    "images": "$inputs.image",
	    "task_type": "<block_does_not_provide_example>",
	    "prompt": "my prompt",
	    "output_structure": {
	        "my_key": "description"
	    },
	    "classes": [
	        "class-a",
	        "class-b"
	    ],
	    "api_key": "xxx-xxx",
	    "model_version": "11B (Free) - OpenRouter",
	    "max_tokens": "<block_does_not_provide_example>",
	    "temperature": "<block_does_not_provide_example>",
	    "max_concurrent_requests": "<block_does_not_provide_example>"
	}
```

</details>