furiosa-ai/Qwen3-VL-32B-Instruct
Qwen3-VL-32B-Instruct is a 32-billion-parameter dense vision-language model from the Qwen3-VL series, developed by Qwen. It integrates a vision encoder with a dense transformer decoder, utilizing Interleaved-MRoPE and DeepStack for multimodal processing. This model excels at visual understanding tasks including OCR, document/chart analysis, spatial reasoning, and video comprehension, and natively supports tool calling. It is specifically optimized for deployment on FuriosaAI RNGD hardware via Furiosa-LLM.
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Qwen3-VL-32B-Instruct: A Dense Vision-Language Model
Qwen3-VL-32B-Instruct is a 32-billion-parameter dense vision-language model from the Qwen3-VL series, developed by Qwen. This model is designed to process both image and text inputs, generating text outputs. It incorporates Interleaved-MRoPE positional embeddings and DeepStack multi-level feature fusion to effectively handle images and videos alongside textual data.
Key Capabilities
- Multimodal Understanding: Processes OpenAI-style multimodal chat messages, accepting
image_urlcontent parts alongside text. - Visual Task Proficiency: Capable of performing various visual understanding tasks, including OCR, document and chart analysis, spatial reasoning, and video comprehension.
- Tool Calling: Natively supports tool (function) calling through the
hermestool-call parser, enabling interaction with external functions. - Hardware Optimization: Provided with a Furiosa Executable Bundle (FXB) for efficient execution on FuriosaAI RNGD hardware, utilizing a tensor-parallel size of 32 PEs across four RNGD cards.
Good For
- Applications requiring advanced visual understanding and reasoning from images and videos.
- Integrating AI models with external tools and functions for complex workflows.
- Deploying high-performance vision-language models on FuriosaAI hardware for optimized inference.