| --- |
| license: other |
| tags: |
| - heal |
| - horizon |
| --- |
| |
| # Qwen3-VL-4B-Instruct |
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| **Original model repository:** [Qwen/Qwen3-VL-4B-Instruct](https://huggingface.co/Qwen/Qwen3-VL-4B-Instruct) |
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| ## Model Introduction |
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| Qwen3-VL-4B-Instruct is an instruction-tuned Vision-Language Model (VLM) for understanding images, videos, and text. It combines a vision encoder with a dense autoregressive language model. The model supports visual question answering, multilingual OCR, document understanding, visual grounding, spatial reasoning, video understanding, visual coding, and visual-agent tasks. |
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| ## Deployment Metrics |
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| ### Model Parameters |
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| | Metric | Value | |
| |---|---:| |
| | Total model parameters | 4.438B | |
| | Vision model (ViT) parameters | 415.3M | |
| | Language model (LM) parameters | 4.022B | |
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| Parameter counts are calculated from the tensors stored in the upstream checkpoint. |
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| ### Performance Metrics |
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| | Chips | Data Type | ViT Image Size | Sequence Length (tokens) | Maximum Context Length (tokens) | BPU Cores (ViT / Prefill / Decode) | ViT Latency (ms) | TTFT (ms) | Prefill TPS (token/s) | Decode TPS (token/s) | BPU Memory (GB) | CPU Memory (GB) | |
| |---|---|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:| |
| | J6P | W8A8 | 448 × 448 | 512 | 1024 | 4 / 4 / 4 | 18.593 | 136.189 | 4,539.468 | 31.398 | 5.6 | 1.6 | |
| | S6P | W8A8 | 448 × 448 | 512 | 1024 | 4 / 4 / 4 | 16.343 | 117.912 | 5,255.315 | 32.677 | 5.9 | 1.6 | |
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| > **Note:** TTFT includes preprocessing and ViT latency. Memory values represent the peak memory usage measured during the specified performance test. |
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