Written by Jakub Rusinowski · Last updated January 6, 2025
Yes, comfortably — you'll have ~6.8 GB of headroom running Phi-4 (14B) at Q4_K_M (9.2 GB, ~73 tok/s (est.)) with room for up to 16K context.
Check price on 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 | 11.6 GB | ✓ Yes | 16K |
| Q4_K_M | 10.1 GB | ✓ Yes | 16K |
| Q3_K_M | 7.6 GB | ✓ Yes | 16K |
| Q2_K | 6.2 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.
| Phi-4 (14B) | Q4_K_M · 9.2 GB · ~73 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 ~6.8 GB of headroom running Phi-4 (14B) at Q4_K_M (9.2 GB, ~73 tok/s (est.)) with room for up to 16K context.
Phi-4 (14B) at Q4_K_M quantization (9.2 GB), estimated ~73 tokens/sec, up to 16K context.
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