Autor: Jakub Rusinowski · Ostatnia aktualizacja: 12 listopada 2024
Yes, comfortably — you'll have ~6.5 GB of headroom running Qwen 2.5 14B Instruct at Q4_K_M (9.5 GB, ~71 tok/s (est.)) with room for up to 32K context.
Sprawdź cenę na Amazon — NVIDIA GeForce RTX 4070 Ti Super 16GB
| VRAM | 16 GB |
| Memory Bandwidth | 672 GB/s |
| Quant | VRAM needed | Fits 16 GB? | Max context |
|---|---|---|---|
| F16 | 29.6 GB | ✗ No | — |
| Q8_0 | 16.5 GB | ✗ No | — |
| Q6_K | 13.1 GB | ✓ Yes | 16K |
| Q5_K_M | 11.5 GB | ✓ Yes | 16K |
| Q4_K_M | 10.1 GB | ✓ Yes | 32K |
| Q3_K_M | 7.6 GB | ✓ Yes | 32K |
| Q2_K | 6.2 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 16 GB. Figures are estimates from parameter count, quantization and memory bandwidth — the analyzer lets you tune KV-cache quant and context.
| Qwen 2.5 14B Instruct | Q4_K_M · 9.5 GB · ~71 tok/s (est.) |
| Qwen 2.5 7B Instruct | Q4_K_M · 4.8 GB · ~140 tok/s (est.) |
At 2 hrs/day, buying (~$799) beats renting at $0.34/hr after about 3.3 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 ~6.5 GB of headroom running Qwen 2.5 14B Instruct at Q4_K_M (9.5 GB, ~71 tok/s (est.)) with room for up to 32K context.
Qwen 2.5 14B Instruct at Q4_K_M quantization (9.5 GB), estimated ~71 tokens/sec, up to 32K context.
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