Autor: Jakub Rusinowski · Ostatnia aktualizacja: 12 lipca 2026
Yes, comfortably — you'll have ~3.3 GB of headroom running Gemma 3n E4B at Q4_K_M (4.7394375 GB, ~72 tok/s (est.)) with room for up to 16K context.
or compare on Vast.ai from $0.35/hr (typical low · varies)
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| VRAM | 8 GB |
| Memory Bandwidth | 272 GB/s |
| Quant | VRAM needed | Fits 8 GB? | Max context |
|---|---|---|---|
| F16 | 17.1 GB | ✗ No | — |
| Q8_0 | 9.7 GB | ✗ No | — |
| Q6_K | 7.8 GB | ✓ Yes | 4K |
| Q5_K_M | 6.9 GB | ✓ Yes | 8K |
| Q4_K_M | 6.1 GB | ✓ Yes | 16K |
| Q3_K_M | 4.7 GB | ✓ Yes | 16K |
| Q2_K | 4 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 8 GB. Figures are estimates from parameter count, quantization and memory bandwidth — the analyzer lets you tune KV-cache quant and context.
| Gemma 3n E4B | Q4_K_M · 4.7394375 GB · ~72 tok/s (est.) |
| Gemma 3n E2B | Q4_K_M · 3.2844 GB · ~113 tok/s (est.) |
At 2 hrs/day, buying (~$299) beats renting at $0.34/hr after about 15 months.
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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 ~3.3 GB of headroom running Gemma 3n E4B at Q4_K_M (4.7394375 GB, ~72 tok/s (est.)) with room for up to 16K context.
Gemma 3n E4B at Q4_K_M quantization (4.7394375 GB), estimated ~72 tokens/sec, up to 16K context.
| Size | VRAM | Verdict | Speed |
|---|---|---|---|
| Gemma 3n E4B | 4.7 GB | Runs | ~72 tok/s |
| Gemma 3n E2B | 3.3 GB | Runs | ~113 tok/s |
← Can I Run It? | Gemma 3n Model Page | NVIDIA GeForce RTX 4060 GPU Page | Check Your Hardware