作者： Jakub Rusinowski · 最后更新： 2025年3月12日
Yes, comfortably — you'll have ~7.9 GB of headroom running Gemma 3 12B Instruct at Q4_K_M (8.1 GB, ~119 tok/s (est.)) with room for up to 16K context.
在亚马逊查看价格 — NVIDIA GeForce RTX 5080 16GB
| VRAM | 16 GB |
| Memory Bandwidth | 960 GB/s |
| Quant | VRAM needed | Fits 16 GB? | Max context |
|---|---|---|---|
| F16 | 26.3 GB | ✗ No | — |
| Q8_0 | 15.1 GB | ✓ Yes | 4K |
| Q6_K | 12.2 GB | ✓ Yes | 8K |
| Q5_K_M | 10.8 GB | ✓ Yes | 16K |
| Q4_K_M | 9.6 GB | ✓ Yes | 16K |
| Q3_K_M | 7.5 GB | ✓ Yes | 16K |
| Q2_K | 6.3 GB | ✓ Yes | 16K |
VRAM needed assumes a 4K-token context with an f16 KV cache; “Max context” is the largest window that still fits in 16 GB. Figures are estimates from parameter count, quantization and memory bandwidth — the analyzer lets you tune KV-cache quant and context.
| Gemma 3 12B Instruct | Q4_K_M · 8.1 GB · ~119 tok/s (est.) |
| Gemma 3 4B Instruct | Q4_K_M · 3.8 GB · ~253 tok/s (est.) |
| Gemma 3 1B Instruct | Q4_K_M · 0.9 GB · ~400 tok/s (est.) |
At 2 hrs/day, buying (~$999) beats renting at $0.34/hr after about 4.1 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 ~7.9 GB of headroom running Gemma 3 12B Instruct at Q4_K_M (8.1 GB, ~119 tok/s (est.)) with room for up to 16K context.
Gemma 3 12B Instruct at Q4_K_M quantization (8.1 GB), estimated ~119 tokens/sec, up to 16K context.
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