Can I run Huihui-Qwen3.8-Flash-Next-abliterated-v2-GGUF on an NVIDIA B300?

Yes, just

Its UD-Q4_K_XL file (223 GB) fits in the 259 GB an NVIDIA B300 can use, with room for ≈ 256K tokens of context.

Full analysis of Huihui-Qwen3.8-Flash-Next-abliterated-v2-GGUF Everything that runs on NVIDIA B300 Get the UD-Q4_K_XL file on Hugging Face

llama-server -hf huihui-ai/Huihui-Qwen3.8-Flash-Next-abliterated-v2-GGUF:UD-Q4_K_XL

Files and context on NVIDIA B300

Each file of Huihui-Qwen3.8-Flash-Next-abliterated-v2-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.

File	Size	On NVIDIA B300	Context (16-bit)	Context (8-bit)
UD-Q4_K_XL	223 GB	Tight	256K	256K
Q8_0	188 GB	Fits	256K	256K
UD-Q6_K_XL	169 GB	Fits	256K	256K
UD-Q5_K_XL	158 GB	Fits	256K	256K
UD-IQ4_XS	93.7 GB	Fits	256K	256K
IQ3_S	83.7 GB	Fits	256K	256K
IQ3_XXS	76.0 GB	Fits	256K	256K
IQ2_XS	68.2 GB	Fits	256K	256K

Huihui-Qwen3.8-Flash-Next-abliterated-v2-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.