Written by Jakub Rusinowski · Last updated July 21, 2026
Yes, comfortably — you'll have ~26.4 GB of headroom running Llama 3.2 Vision 90B at Q4_K_M (53.613 GB, ~29 tok/s (est.)) with room for up to 32K context.
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| VRAM | 80 GB |
| Memory Bandwidth | 2000 GB/s |
| Quant | VRAM needed | Fits 80 GB? | Max context |
|---|---|---|---|
| F16 | 180.1 GB | ✗ No | — |
| Q8_0 | 96.8 GB | ✗ No | — |
| Q6_K | 75.3 GB | ✓ Yes | 8K |
| Q5_K_M | 65.4 GB | ✓ Yes | 32K |
| Q4_K_M | 56.1 GB | ✓ Yes | 32K |
| Q3_K_M | 40.3 GB | ✓ Yes | 64K |
| Q2_K | 31.7 GB | ✓ Yes | 64K |
VRAM needed assumes a 4K-token context with an f16 KV cache; “Max context” is the largest window that still fits in 80 GB. Figures are estimates from parameter count, quantization and memory bandwidth — the analyzer lets you tune KV-cache quant and context.
| Llama 3.2 Vision 90B | Q4_K_M · 53.613 GB · ~29 tok/s (est.) |
| Llama 3.2 Vision 11B | Q4_K_M · 6.39975 GB · ~156 tok/s (est.) |
At 2 hrs/day, buying (~$25,000) beats renting at $0.77/hr after about 45.1 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 ~26.4 GB of headroom running Llama 3.2 Vision 90B at Q4_K_M (53.613 GB, ~29 tok/s (est.)) with room for up to 32K context.
Llama 3.2 Vision 90B at Q4_K_M quantization (53.613 GB), estimated ~29 tokens/sec, up to 32K context.
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