Can I Run Llama 3.2 Vision on NVIDIA GeForce RTX 4070 Super?
Written by Jakub Rusinowski · Last updated September 29, 2026
Yes, comfortably — Llama 3.2 Vision 11B 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 Vision 11B 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 Vision 11B on 8 GB of system RAM, CPU only: runs.
Llama 3.2 Vision Sizes That Fit the NVIDIA GeForce RTX 4070 Super (at 8K context)
| Llama 3.2 Vision 11B | Q4_K_M · 8.5 GB at 8K context · ~58 tok/s (est.) |
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FAQ
Will Llama 3.2 Vision run on the NVIDIA GeForce RTX 4070 Super?
Yes, comfortably — Llama 3.2 Vision 11B 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.
Which Llama 3.2 Vision variant fits best on the NVIDIA GeForce RTX 4070 Super?
Llama 3.2 Vision 11B 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 Vision size on the NVIDIA GeForce RTX 4070 Super
| Size | VRAM at 8K | Verdict | Speed |
|---|---|---|---|
| Llama 3.2 Vision 90B | 57.8 GB | Does not fit | — |
| Llama 3.2 Vision 11B | 8.5 GB | Runs | ~58 tok/s |
Llama 3.2 Vision on Other GPUs
- Llama 3.2 Vision on NVIDIA GeForce RTX 5070
- Llama 3.2 Vision on NVIDIA GeForce RTX 4070 Ti
- Llama 3.2 Vision on NVIDIA GeForce RTX 4070
- Llama 3.2 Vision on NVIDIA GeForce RTX 3060 (12GB)
- Llama 3.2 Vision on Intel Arc B580
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