Can the RTX 5080 run Qwen3 14B?

Yes. Qwen3 14B fits the RTX 5080's 16 GB at Q4_K_M (about 9.8 GB needed), running at an estimated 69 tok/s. There's room for up to Q5_K_M if you want higher quality.

VRAM
16 GB
Needs at Q4
9.8 GB
Headroom
6.2 GB
Speed (Q4_K_M)
~69 tok/s

Every quantization

Qwen3 14B (14B) on 16 GB

QuantWeightsNeedsFitEst. speed
Q4_K_M8 GB9.8 GBFits~69 tok/s
Q5_K_M10 GB11.8 GBFits~55 tok/s
Q8_016 GB17.8 GBToo big -
FP1628 GB29.8 GBToo big -

Estimates. Needs = weights + 1.8 GB for KV cache and runtime at modest context. Speed is single-stream decode scaled from the RTX 5080's 960 GB/s bandwidth (Estimated from memory bandwidth (llama.cpp decode)). Long contexts need more memory and run slower.

Run it

Copy, paste, go

ollama run qwen3:14b
llama-server -hf Qwen/Qwen3-14B-GGUF -ngl 99

Ollama pulls a Q4 build by default. Pick a larger quant only if the table above says it fits. Full Qwen3 14B details →

Compare

Same model, other hardware - and other models on this card

Qwen3 14B on other hardware

Also runs on the RTX 5080

Frequently asked

Quick answers

Can the NVIDIA RTX 5080 run Qwen3 14B?

Yes. Qwen3 14B fits the RTX 5080's 16 GB at Q4_K_M (about 9.8 GB needed), running at an estimated 69 tok/s. There's room for up to Q5_K_M if you want higher quality.

How much VRAM does Qwen3 14B need?

About 8 GB of weights at Q4_K_M, 16 GB at Q8_0 and 28 GB at FP16. Add roughly 1.8 GB for the KV cache and runtime at modest context lengths.

How fast is Qwen3 14B on the RTX 5080?

Roughly 69 tokens per second at Q4_K_M (single user, llama.cpp-style decode). This is an estimate from the RTX 5080's 960 GB/s memory bandwidth.