Autor: Jakub Rusinowski · Ostatnia aktualizacja: 15 sierpnia 2026
Yes, comfortably — you'll have ~3.6 GB of headroom running Llama 3.2 11B Vision Instruct at Q4_K_M (6.39975 GB, ~58 tok/s (est.)) with room for up to 16K context.
or compare on Vast.ai from $0.35/hr (typical low · varies)
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| VRAM | 10 GB |
| Memory Bandwidth | 760 GB/s |
| Quant | VRAM needed | Fits 10 GB? | Max context |
|---|---|---|---|
| F16 | 22.7 GB | ✗ No | — |
| Q8_0 | 12.7 GB | ✗ No | — |
| Q6_K | 10.2 GB | ✗ No | — |
| Q5_K_M | 9 GB | ✓ Yes | 8K |
| Q4_K_M | 7.9 GB | ✓ Yes | 16K |
| Q3_K_M | 6 GB | ✓ Yes | 16K |
| Q2_K | 5 GB | ✓ Yes | 32K |
VRAM needed assumes a 4K-token context with an f16 KV cache; “Max context” is the largest window that still fits in 10 GB. Figures are estimates from parameter count, quantization and memory bandwidth — the analyzer lets you tune KV-cache quant and context.
| Llama 3.2 11B Vision Instruct | Q4_K_M · 6.39975 GB · ~58 tok/s (est.) |
| Llama 3.2 3B Instruct | Q4_K_M · 1.9380375 GB · ~136 tok/s (est.) |
| Llama 3.2 1B Instruct | Q4_K_M · 0.74865 GB · ~243 tok/s (est.) |
At 2 hrs/day, buying (~$699) beats renting at $0.34/hr after about 2.9 years.
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Cloud rates verified 2026-07 — estimates, and marketplace prices vary. Buying price is GPU MSRP only, not a full PC.
Yes, comfortably — you'll have ~3.6 GB of headroom running Llama 3.2 11B Vision Instruct at Q4_K_M (6.39975 GB, ~58 tok/s (est.)) with room for up to 16K context.
Llama 3.2 11B Vision Instruct at Q4_K_M quantization (6.39975 GB), estimated ~58 tokens/sec, up to 16K context.
| Size | VRAM | Verdict | Speed |
|---|---|---|---|
| Llama 3.2 90B Vision Instruct | 53.6 GB | Does not fit | — |
| Llama 3.2 11B Vision Instruct | 6.4 GB | Runs | ~58 tok/s |
| Llama 3.2 3B Instruct | 1.9 GB | Runs | ~136 tok/s |
| Llama 3.2 1B Instruct | 0.7 GB | Runs | ~243 tok/s |
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