Can I run Gemma4-26B-A4B-QAT-Uncensored-HauhauCS-Balanced-MTP on an RTX 4090?

Yes

Its Q4_K_M file (16.8 GB) fits in the 21.6 GB an RTX 4090 can use, with room for ≈ 52K tokens of context.

Full analysis of Gemma4-26B-A4B-QAT-Uncensored-HauhauCS-Balanced-MTP Everything that runs on RTX 4090 Get the Q4_K_M file on Hugging Face

ollama run hf.co/HauhauCS/Gemma4-26B-A4B-QAT-Uncensored-HauhauCS-Balanced-MTP:Q4_K_M

Files and context on RTX 4090

Each file of Gemma4-26B-A4B-QAT-Uncensored-HauhauCS-Balanced-MTP (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 RTX 4090	Context (16-bit)	Context (8-bit)
Q4_K_M	16.8 GB	Fits	52K	110K

Gemma4-26B-A4B-QAT-Uncensored-HauhauCS-Balanced-MTP on other hardware

NVIDIA H100Yes
RTX 5090Yes
RTX 4090Yes
RTX 3090Yes
RTX 5060 Ti 16 GBNo
RTX 3060 12 GBNo
RTX 4060No
Mac with 32 GBYes
Mac with 64 GBYes
Mac with 128 GBYes

Popular models that run on RTX 4090

Qwen3-0.6BQwen · 752M
Qwen3-VL-8B-InstructQwen · 8.77B
gpt2openai-community · 137M
Qwen3-8BQwen · 8.19B
Qwen3-Coder-30B-A3B-Instruct-GGUFunsloth · 30.5B
Qwen2.5-7B-InstructQwen · 7.62B
Qwen3.5-9BQwen · 9.65B
Qwen2.5-0.5B-InstructQwen · 494M

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.