| --- |
| license: other |
| tags: |
| - heal |
| - horizon |
| --- |
| |
| # Qwen3-VL-8B-Instruct |
|
|
| **Original model repository:** [Qwen/Qwen3-VL-8B-Instruct](https://huggingface.co/Qwen/Qwen3-VL-8B-Instruct) |
|
|
| ## Model Introduction |
|
|
| Qwen3-VL-8B-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. |
|
|
| ## Deployment Metrics |
|
|
| ### Model Parameters |
|
|
| | Metric | Value | |
| |---|---:| |
| | Total model parameters | 8.767B | |
| | Vision model (ViT) parameters | 576.4M | |
| | Language model (LM) parameters | 8.191B | |
|
|
| Parameter counts are calculated from the tensors stored in the upstream checkpoint. |
|
|
| ### Performance Metrics |
|
|
| | 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 | 28.593 | 193.200 | 3,211.139 | 19.840 | 9.4 | 2.5 | |
| | S6P | W8A8 | 448 × 448 | 512 | 1024 | 4 / 4 / 4 | 25.396 | 164.228 | 3,807.482 | 20.613 | 9.6 | 2.5 | |
| | S6P | W4A8 | 448 × 448 | 512 | 1024 | 4 / 4 / 4 | 25.111 | 159.716 | 3,928.261 | 31.789 | 6.4 | 2.5 | |
|
|
| > **Note:** TTFT includes preprocessing and ViT latency. Memory values represent the peak memory usage measured during the specified performance test. |
|
|
