Can I run Qwen3.5-9B-AWQ on an RTX 5080?

Yes, just

Its published weights (12.4 GB) fit in the 14.4 GB an RTX 5080 can use, with room for ≈ 59K tokens of context.

Full analysis of Qwen3.5-9B-AWQ Everything that runs on RTX 5080 Get the weights on Hugging Face

hf download QuantTrio/Qwen3.5-9B-AWQ

Files and context on RTX 5080

Each file of Qwen3.5-9B-AWQ (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 5080	Context (16-bit)	Context (8-bit)
As published	12.4 GB	Tight	59K	118K
4-bit (estimate)	5.43 GB	Fits	256K	256K

Qwen3.5-9B-AWQ on other hardware

NVIDIA H100Yes
RTX 5090Yes
RTX 4090Yes
RTX 3090Yes
RTX 5080Yes, just
RTX 5060 Ti 16 GBYes, just
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 5080

Qwen3-0.6BQwen · 752M
gpt2openai-community · 137M
Qwen3-Coder-30B-A3B-Instruct-GGUFunsloth · 30.5B
Qwen2.5-0.5B-InstructQwen · 494M
Qwen2.5-1.5B-InstructQwen · 1.54B
Qwen3-4BQwen · 4.02B
Qwen3.5-4BQwen · 4.66B
gpt-oss-20bopenai · 20.9B

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.