---
license: apache-2.0
base_model: Qwen/Qwen3-VL-2B-Instruct
pipeline_tag: image-text-to-text
tags:
  - core-ai
  - coreai-models
  - ios
  - vision-language-model
---

# Qwen3-VL 2B Instruct for Core AI

[Qwen/Qwen3-VL-2B-Instruct](https://huggingface.co/Qwen/Qwen3-VL-2B-Instruct) exported with the [apple/coreai-models](https://github.com/apple/coreai-models) 1.0.0 VLM recipe, for `CoreAIVisionLanguageModel` (`CoreAILanguageModels`) and [`@react-native-ai/core-ai`](https://github.com/callstackincubator/ai/tree/main/packages/core-ai).

## Folder

`qwen3_vl_2b/` is the bundle (`metadata.json` `kind: "vlm"`), 2.7 GB:

| File                  | Role                                                     | Size   |
| --------------------- | -------------------------------------------------------- | ------ |
| `qwen3_vl_2b.aimodel` | Text decoder, 4-bit weights, stateful KV cache (4096)    | 923 MB |
| `vision.aimodel`      | Vision encoder, 448x448 input, 196 image tokens, float16 | 1.2 GB |
| `embed.aimodel`       | Token embeddings                                         | 594 MB |
| `tokenizer/`          | Hugging Face tokenizer                                   | 11 MB  |

## Platforms

- **iOS 27 (iPhone 17 Pro)**: works with the [increased memory limit](https://developer.apple.com/documentation/bundleresources/entitlements/com.apple.developer.kernel.increased-memory-limit) entitlement, which raises the app limit from 3,376 MB to 6,144 MB. Without it the app aborts while MPSGraph loads the weights. Answering three questions about a 320x240 photo, including loading the model, took 39 s.
- **macOS 27**: the recipe's target format.

The VLM recipe has no iOS preset, so this is the macOS export format (one `main` function per model, run on the GPU).

## Export

```bash
git clone https://github.com/apple/coreai-models && cd coreai-models && git checkout 1.0.0
uv run coreai.vlm.export qwen3-vl --compression 4bit
```

In 1.0.0, `--compression 4bit` fails with `build_reference_inputs returned keys ['input_ids', ...], which are not a contiguous in-order prefix of forward's parameters ['inputs_embeds', ...]`, because `Qwen3VLForCausalLMEmbeddings` inherits token-id reference inputs. This export overrides `export_input_names`, `build_reference_inputs` and `build_dynamic_shapes` in `python/src/coreai_models/models/macos/qwen3_vl.py` to trace `inputs_embeds` (random `[1, query_len, hidden_size]` tensors) in place of `input_ids`. The model code is otherwise unchanged.

## Use

```ts
import { coreAI } from '@react-native-ai/core-ai'
import { generateText } from 'ai'

const model = coreAI.languageModel({
  id: 'qwen3-vl-2b',
  source: { type: 'file', uri: bundleFolder },
})

const { text } = await generateText({
  model,
  messages: [
    {
      role: 'user',
      content: [
        { type: 'file', mediaType: 'image/jpeg', data: new URL(`file://${imagePath}`) },
        { type: 'text', text: 'What animals are in this picture?' },
      ],
    },
  ],
})
```

Apple's VLM engine reads the first image of the prompt, decodes greedily, and needs an image in every prompt.

## License

Apache-2.0, as the [base model](https://huggingface.co/Qwen/Qwen3-VL-2B-Instruct).