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

Can I run Sage-A1.5-Q4_K_M-GGUF on an RTX 3090?

No

Even its smallest file (Q4_K_M, 21.7 GB) is more than an RTX 3090 can hold (21.6 GB usable): it needs 2 of them.

Full analysis of Sage-A1.5-Q4_K_M-GGUF Everything that runs on RTX 3090

Files and context on RTX 3090

Each file of Sage-A1.5-Q4_K_M-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 3090 Context (16-bit)Context (8-bit)
Q4_K_M21.7 GBDoesn't fit——

Sage-A1.5-Q4_K_M-GGUF on other hardware

Popular models that run on RTX 3090

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.