Can the GeForce RTX 5090 run Llama 3.2 1B Instruct?
Fits comfortably at Q4_K_M.
Llama 3.2 1B Instruct is 1.23B parameters. At Q4_K_M the weights are about 0.7 GiB; with the 1.5 GiB runtime reserve that is 2.2 GiB against the card's 32GB, leaving about 29.8 GiB for context.
All three quants
32GB card| Quant | Weights | With reserve | Verdict | Headroom |
|---|---|---|---|---|
| Q4_K_Mthe everyday quant | 0.7 GiB | 2.2 GiB | Fits comfortably | 29.8 GiB |
| Q8_0near-lossless | 1.2 GiB | 2.7 GiB | Fits comfortably | 29.3 GiB |
| FP16full weights | 2.3 GiB | 3.8 GiB | Fits comfortably | 28.2 GiB |
Verdict rules: fits comfortably when weights plus reserve sit within 85% of VRAM; tight when they fit with little left for context; CPU offload when they exceed VRAM by up to 2x (runs, slowly, with layers in system RAM); no beyond that. The KV cache per token depends on the model's architecture and is not modelled here.
Good match. Get the card.
The GeForce RTX 5090 clears Llama 3.2 1B Instruct at Q4_K_M and at Q8_0. Live listings below; this page was rebuilt 2026-08-23.
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About the model
Llama 3.2 1B Instruct by Meta: 131,072-token native context, text, released 2024 under the Llama 3.2 Community License. Model card → · Hosted pricing on PicksByModel →