| --- |
| license: other |
| tags: |
| - heal |
| - horizon |
| --- |
| |
| # Qwen2.5-VL-7B-Instruct |
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| **Original model repository:** [Qwen/Qwen2.5-VL-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-7B-Instruct) |
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| ## Model Introduction |
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| Qwen2.5-VL-7B-Instruct is an instruction-tuned Vision-Language Model (VLM) for understanding images, videos, and text. It combines a vision transformer with the Qwen2.5 language model and supports visual question answering, OCR, document and chart analysis, visual localization, image description, video understanding, 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 | 8.292B | |
| | Vision model (ViT) parameters | 676.6M | |
| | Language model (LM) parameters | 7.616B | |
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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 | 43.234 | 200.656 | 3,336.058 | 21.190 | 8.3 | 2.2 | |
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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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