Can I run pythia-6.9b on an RTX 4090?

Yes

Its published weights (13.8 GB) fit in the 21.6 GB an RTX 4090 can use, with room for ≈ 2K tokens of context.

Full analysis of pythia-6.9b Everything that runs on RTX 4090 Get the weights on Hugging Face

hf download EleutherAI/pythia-6.9b

Files and context on RTX 4090

Each file of pythia-6.9b (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)
As published	13.8 GB	Fits	2K	2K
4-bit (estimate)	3.93 GB	Fits	2K	2K

pythia-6.9b on other hardware

NVIDIA H100Yes
RTX 5090Yes
RTX 4090Yes
RTX 3090Yes
RTX 5060 Ti 16 GBProbably, at 4-bit
RTX 3060 12 GBProbably, at 4-bit
RTX 4060Probably, at 4-bit
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
tiny-Qwen2ForCausalLM-2.5trl-internal-testing · 2.44M
Qwen3-8BQwen · 8.19B
Qwen3-Coder-30B-A3B-Instruct-GGUFunsloth · 30.5B
Qwen2.5-7B-InstructQwen · 7.62B
Qwen3.5-9BQwen · 9.65B

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.