Autor: Jakub Rusinowski · Ostatnia aktualizacja: 11 września 2026
Yes. Llama 3.2 3B Instruct needs 1.9 GB at Q4_K_M and the NVIDIA GeForce RTX 4070 has 12 GB, leaving about 10.1 GB of headroom, at roughly 135 tok/s (estimated) with room for up to 64K of context.
See what else this hardware can run →
| Model | Llama 3.2 3B Instruct |
| Parameters | 3B |
| Quantization | Q4_K_M |
| VRAM needed | 1.9 GB |
| NVIDIA GeForce RTX 4070 VRAM | 12 GB |
| Verdict | Runs |
| Max context | 64K |
| Estimated speed | ~135 tok/s |
| Quant | VRAM needed | Fits 12 GB? | Max context | Whole PC |
|---|---|---|---|---|
| F16 | 7.7 GB | ✓ Yes | 32K | — |
| Q8_0 | 4.7 GB | ✓ Yes | 64K | — |
| Q6_K | 3.9 GB | ✓ Yes | 64K | — |
| Q5_K_M | 3.5 GB | ✓ Yes | 64K | — |
| Q4_K_M | 3.2 GB | ✓ Yes | 64K | — |
| Q3_K_M | 2.6 GB | ✓ Yes | 64K | — |
| Q2_K | 2.3 GB | ✓ Yes | 64K | — |
Assumes a 4K-token context with an f16 KV cache. A longer window needs more; a quantized KV cache needs less. “Max context” is the largest window that still fits in 12 GB. Figures are estimates from parameter count, quantization and memory bandwidth — the analyzer lets you tune KV-cache quant and context.
Context costs VRAM too. At Q4_K_M on the NVIDIA GeForce RTX 4070: 8K 3.7 GB · 32K 6.5 GB · 125K 17.4 GB ✗. Past 125K it no longer fits 12 GB — a q8_0 KV cache buys roughly half of that back, which the calculator will price for you.
Nothing to change — run it at Q4_K_M. If you want more capability, check whether the next size up also fits.
No compatible GPU? Llama 3.2 3B Instruct on 8 GB of system RAM, CPU only: runs.
Running Llama 3.2 3B Instruct on this card:
At 2 hrs/day, buying (~$599) beats renting at $0.34/hr after about 2.4 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.
All Llama 3.2 Family sizes on the NVIDIA GeForce RTX 4070 | Llama 3.2 3B Instruct model page | NVIDIA GeForce RTX 4070 GPU page | Check your hardware