Model Anatomy See what's inside open-weight AI models

Can I run Qwen3-VL-4B-Instruct-GGUF on an NVIDIA B300?

Yes

Its F16 file (8.05 GB) fits in the 259 GB an NVIDIA B300 can use, with room for ≈ 256K tokens of context.

Full analysis of Qwen3-VL-4B-Instruct-GGUF Everything that runs on NVIDIA B300 Get the F16 file on Hugging Face
ollama run hf.co/Qwen/Qwen3-VL-4B-Instruct-GGUF:F16

Files and context on NVIDIA B300

Each file of Qwen3-VL-4B-Instruct-GGUF (and of GGUF versions the site has analyzed), and how much context fits next to it, with the context cache in 16-bit or 8-bit.

FileSizeOn NVIDIA B300 Context (16-bit)Context (8-bit)
F168.05 GBFits256K256K
Q8_04.28 GBFits256K256K
Q4_K_M2.50 GBFits256K256K

Qwen3-VL-4B-Instruct-GGUF on other hardware

Popular models that run on NVIDIA B300

Assumes 90% of the card's memory is usable and at least 4K tokens of context for one conversation, with the context cache in 16-bit unless noted. Fits leaves at least 20% of that memory for context; Tight leaves less.