With 8 GB of VRAM, the RTX 4060 Ti 8 GB runs Llama 3.2 1B Instruct at Q4_K_M entirely on the GPU with an 8K context (about 2 GB needed). At Q8_0 it fits entirely.
Q4_K_M · 8K context
The model needs about 2 GB and fits in the 7.7 GB available, with 5.6 GB to spare.
~2 GB (1.7 GB–2.3 GB) needed · estimate
Fits entirely in VRAM · 5.6 GB left
EstimateData updated 24 days agoSource: Run LLM Locally engine, Hugging Face config.json + model card
What makes this estimate less reliable
| Llama 3.2 1B Instruct Q8_08K~2.5 GB · 133–184 tok/s estimate | Excellent |
|---|---|
| Llama 3.2 1B Instruct Q6_K8K~2.2 GB · 163–228 tok/s estimate | Excellent |
| Llama 3.2 1B Instruct Q5_K_M8K~2.1 GB · 177–250 tok/s estimate | Excellent |
| Llama 3.2 1B Instruct Q4_K_M8K~2 GB · 193–275 tok/s estimate | Excellent |
| Llama 3.2 1B Instruct IQ4_XS8K~2 GB · 204–294 tok/s estimate | Excellent |
| Llama 3.2 1B Instruct Q3_K_M8K~1.9 GB · 214–311 tok/s estimate | Excellent |
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8 GB GDDR6 · 288 GB/s · 160 W
ExcellentRuns Llama 3.2 1B Instruct Q4_K_M entirely in memory
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