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

Can I run gemma-4-12B-coder-fable5-composer2.5-v1-GGUF on an RTX 3090?

Yes

Its Q8_0 file (12.7 GB) fits in the 21.6 GB an RTX 3090 can use, with room for ≈ 62K tokens of context.

Full analysis of gemma-4-12B-coder-fable5-composer2.5-v1-GGUF Everything that runs on RTX 3090 Get the Q8_0 file on Hugging Face
ollama run hf.co/yuxinlu1/gemma-4-12B-coder-fable5-composer2.5-v1-GGUF:Q8_0

Files and context on RTX 3090

Each file of gemma-4-12B-coder-fable5-composer2.5-v1-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)
Q8_012.7 GBFits62K128K
Q6_K9.79 GBFits83K171K
Q4_K_M7.38 GBFits101K207K
Q3_K_M6.09 GBFits111K226K
Q2_K4.83 GBFits120K245K

gemma-4-12B-coder-fable5-composer2.5-v1-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.