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

Can I run Qwen3-VL-30B-A3B-Instruct-GGUF on an RTX 5090?

Yes

Its Q4_K_M file (18.6 GB) fits in the 28.8 GB an RTX 5090 can use, with room for ≈ 102K tokens of context.

Full analysis of Qwen3-VL-30B-A3B-Instruct-GGUF Everything that runs on RTX 5090 Get the Q4_K_M file on Hugging Face
ollama run hf.co/Qwen/Qwen3-VL-30B-A3B-Instruct-GGUF:Q4_K_M

Files and context on RTX 5090

Each file of Qwen3-VL-30B-A3B-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 RTX 5090 Context (16-bit)Context (8-bit)
F1661.1 GBDoesn't fit——
Q8_032.5 GBDoesn't fit——
Q4_K_M18.6 GBFits102K204K

Qwen3-VL-30B-A3B-Instruct-GGUF on other hardware

Popular models that run on RTX 5090

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.