Autor: Jakub Rusinowski · Ostatnia aktualizacja: 27 czerwca 2024
Yes, comfortably — you'll have ~9.2 GB of headroom running Gemma 2 9B IT at Q4_K_M (6.8 GB, ~42 tok/s (est.)) with room for up to 8K context.
Sprawdź cenę na Amazon — NVIDIA GeForce RTX 4060 Ti 16GB
| VRAM | 16 GB |
| Memory Bandwidth | 288 GB/s |
| Quant | VRAM needed | Fits 16 GB? | Max context |
|---|---|---|---|
| F16 | 20.2 GB | ✗ No | — |
| Q8_0 | 11.8 GB | ✓ Yes | 8K |
| Q6_K | 9.6 GB | ✓ Yes | 8K |
| Q5_K_M | 8.6 GB | ✓ Yes | 8K |
| Q4_K_M | 7.6 GB | ✓ Yes | 8K |
| Q3_K_M | 6 GB | ✓ Yes | 8K |
| Q2_K | 5.2 GB | ✓ Yes | 8K |
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 2 9B IT | Q4_K_M · 6.8 GB · ~42 tok/s (est.) |
At 2 hrs/day, buying (~$499) beats renting at $0.34/hr after about 2.0 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 ~9.2 GB of headroom running Gemma 2 9B IT at Q4_K_M (6.8 GB, ~42 tok/s (est.)) with room for up to 8K context.
Gemma 2 9B IT at Q4_K_M quantization (6.8 GB), estimated ~42 tokens/sec, up to 8K context.
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