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

Can I run Nanbeige4.3-33B-GGUF on an NVIDIA B300?

Yes

Its Q8_0 file (35.2 GB) fits in the 259 GB an NVIDIA B300 can use, with room for ≈ 512K tokens of context.

Full analysis of Nanbeige4.3-33B-GGUF Everything that runs on NVIDIA B300 Get the Q8_0 file on Hugging Face
ollama run hf.co/AtomicChat/Nanbeige4.3-33B-GGUF:Q8_0

Files and context on NVIDIA B300

Each file of Nanbeige4.3-33B-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)
Q8_035.2 GBFits512K512K
Q6_K30.1 GBFits512K512K
Q5_K27.9 GBFits512K512K
Q5_K_M24.7 GBFits512K512K
Nanbeige4.3-33B-Q5_K_M23.5 GBFits512K512K
Nanbeige4.3-33B-AD-Q5_K_M-Q4_K_M22.6 GBFits512K512K
Q4_K_M21.2 GBFits512K512K
IQ4_XS20.3 GBFits512K512K
IQ3_S17.1 GBFits512K512K
IQ3_XXS14.9 GBFits512K512K
IQ2_S13.7 GBFits512K512K

Nanbeige4.3-33B-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.