Autor: Jakub Rusinowski · Ostatnia aktualizacja: 3 czerwca 2026
Yes, comfortably — you'll have ~6 GB of headroom running Gemma 4 12B (Unified) at Q4_K_M (10 GB, ~67 tok/s (est.)) with room for up to 8K 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 | 28.6 GB | ✗ No | — |
| Q8_0 | 17.4 GB | ✗ No | — |
| Q6_K | 14.5 GB | ✓ Yes | 4K |
| Q5_K_M | 13.1 GB | ✓ Yes | 4K |
| Q4_K_M | 11.9 GB | ✓ Yes | 8K |
| Q3_K_M | 9.8 GB | ✓ Yes | 8K |
| Q2_K | 8.6 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 4 12B (Unified) | Q4_K_M · 10 GB · ~67 tok/s (est.) |
| Gemma 4 E4B | Q4 (QAT) · 5.5 GB · ~122 tok/s (est.) |
| Gemma 4 E2B | Q4 (QAT) · 5 GB · ~134 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 GB of headroom running Gemma 4 12B (Unified) at Q4_K_M (10 GB, ~67 tok/s (est.)) with room for up to 8K context.
Gemma 4 12B (Unified) at Q4_K_M quantization (10 GB), estimated ~67 tokens/sec, up to 8K context.
← Can I Run It? | Gemma 4 Model Page | NVIDIA GeForce RTX 4070 Ti Super GPU Page | Check Your Hardware