Can I Run Llama 3.2 Family on NVIDIA GeForce RTX 4070 Super?
Written by Jakub Rusinowski · Last updated September 29, 2026
Yes, comfortably — Llama 3.2 11B Vision Instruct at Q4_K_M needs 8.5 GB at 8K context (6.4 GB weights + 2.1 GB KV cache/overhead), leaving ~3.5 GB of the NVIDIA GeForce RTX 4070 Super's 12 GB, at ~58 tok/s (est.), with room for up to 16K context.
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NVIDIA GeForce RTX 4070 Super Specs
| VRAM | 12 GB |
| Memory Bandwidth | 504 GB/s |
Llama 3.2 11B Vision Instruct on the NVIDIA GeForce RTX 4070 Super: VRAM by quantization
| Quant | VRAM needed | Fits 12 GB? | Max context | Whole PC |
|---|---|---|---|---|
| F16 | 23.3 GB | ✗ No | — | — |
| Q8_0 | 13.4 GB | ✗ No | — | — |
| Q6_K | 10.8 GB | ✓ Yes | 8K | — |
| Q5_K_M | 9.7 GB | ✓ Yes | 16K | — |
| Q4_K_M | 8.5 GB | ✓ Yes | 16K | — |
| Q3_K_M | 6.7 GB | ✓ Yes | 32K | — |
| Q2_K | 5.6 GB | ✓ Yes | 32K | — |
Assumes an 8K-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 Super: 8K 8.5 GB · 32K 12.6 GB ✗ · 125K 28.2 GB ✗. Past 32K it no longer fits 12 GB — a q8_0 KV cache buys roughly half of that back, which the calculator will price for you.
No compatible GPU? Llama 3.2 11B Vision Instruct on 16 GB of system RAM, CPU only: runs.
Llama 3.2 Family Sizes That Fit the NVIDIA GeForce RTX 4070 Super (at 8K context)
| Llama 3.2 11B Vision Instruct | Q4_K_M · 8.5 GB at 8K context · ~58 tok/s (est.) |
| Llama 3.2 3B Instruct | Q4_K_M · 3.7 GB at 8K context · ~135 tok/s (est.) |
| Llama 3.2 1B Instruct | Q4_K_M · 1.8 GB at 8K context · ~242 tok/s (est.) |
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.
FAQ
Can I run Llama 3.2 Family on the NVIDIA GeForce RTX 4070 Super?
Yes, comfortably — Llama 3.2 11B Vision Instruct at Q4_K_M needs 8.5 GB at 8K context (6.4 GB weights + 2.1 GB KV cache/overhead), leaving ~3.5 GB of the NVIDIA GeForce RTX 4070 Super's 12 GB, at ~58 tok/s (est.), with room for up to 16K context.
What's the best Llama 3.2 Family size for the NVIDIA GeForce RTX 4070 Super?
Llama 3.2 11B Vision Instruct at Q4_K_M quantization needs 8.5 GB at 8K context (6.4 GB weights + 2.1 GB KV cache/overhead), estimated ~58 tokens/sec, up to 16K context.
Every Llama 3.2 Family size on the NVIDIA GeForce RTX 4070 Super
| Size | VRAM at 8K | Verdict | Speed |
|---|---|---|---|
| Llama 3.2 90B Vision Instruct | 57.8 GB | Does not fit | — |
| Llama 3.2 11B Vision Instruct | 8.5 GB | Runs | ~58 tok/s |
| Llama 3.2 3B Instruct | 3.7 GB | Runs | ~135 tok/s |
| Llama 3.2 1B Instruct | 1.8 GB | Runs | ~242 tok/s |
Llama 3.2 Family on Other GPUs
- Llama 3.2 Family on NVIDIA GeForce RTX 5070
- Llama 3.2 Family on NVIDIA GeForce RTX 4070 Ti
- Llama 3.2 Family on NVIDIA GeForce RTX 4070
- Llama 3.2 Family on NVIDIA GeForce RTX 3060 (12GB)
- Llama 3.2 Family on Intel Arc B580
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VRAM Tier
Troubleshooting
Buying Guide
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