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

Can I run GLM-5.3-Flash-abliterated-GGUF on an NVIDIA B200?

Yes

Its UD-IQ1_S file (93.1 GB) fits in the 162 GB an NVIDIA B200 can use, with room for an unknown amount of context. That file is under 3 bits per weight, so expect noticeably lower quality.

Full analysis of GLM-5.3-Flash-abliterated-GGUF Everything that runs on NVIDIA B200 Get the UD-IQ1_S file on Hugging Face
llama-server -hf huihui-ai/GLM-5.3-Flash-abliterated-GGUF:UD-IQ1_S

Files and context on NVIDIA B200

Each file of GLM-5.3-Flash-abliterated-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 B200 Context (16-bit)Context (8-bit)
UD-Q4_K_XL200 GBDoesn't fit——
UD-IQ4_XS157 GBDoesn't fit——
UD-IQ1_S93.1 GBFitsnot knownnot known

GLM-5.3-Flash-abliterated-GGUF on other hardware

Popular models that run on NVIDIA B200

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.