Can I Run Llama 3.2 Vision on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM)?
Written by Jakub Rusinowski · Last updated September 25, 2024
Yes
Yes — Llama 3.2 Vision 11B at Q3_K_M needs about 6.7 GB of the 8 GB usable on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM) (~1.3 GB spare), at ~34.2 tok/s (estimated), with room for about 8,192 tokens of context.
Confidence: high · Recommended quantization: Q3_K_M · Estimated speed: ~34.2 tok/s
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RTX 4060 Laptop (8 GB VRAM, 16 GB RAM) — what it gives a model
| Usable memory for models | 8 GB |
| Memory bandwidth | 256 GB/s |
| Form factor | Laptop |
| Operating system | Windows or Linux |
| Memory upgradeable | Yes |
| Price | $1,099 (lib/data/laptops.ts (street price), checked 2026-07-06) |
Llama 3.2 Vision on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM): memory by quantization
| Quant | Memory needed | Fits 8 GB? | Max context | Est. speed | Download |
|---|---|---|---|---|---|
| F16 | 23.3 GB | ✗ No | — | — | 21.2 GB |
| Q8_0 | 13.4 GB | ✗ No | — | — | 11.3 GB |
| Q6_K | 10.8 GB | ✗ No | — | — | 8.7 GB |
| Q5_K_M | 9.7 GB | ✗ No | — | — | 7.5 GB |
| Q4_K_M | 8.5 GB | ✗ No | — | — | 6.4 GB |
| Q3_K_M | 6.7 GB | ✓ Yes | 8K | ~34.2 tok/s | 4.5 GB |
| Q2_K | 5.6 GB | ✓ Yes | 16K | ~41.9 tok/s | 3.5 GB |
Which Llama 3.2 Vision sizes fit
| Variant | Needs at Q4_K_M | Fits? | Est. speed |
|---|---|---|---|
| Llama 3.2 Vision 90B | 57.8 GB | ✗ Too large | — |
| Llama 3.2 Vision 11B | 8.5 GB | ✗ Too large | — |
What to watch out for
- Only ~1.3 GB of headroom at Q3_K_M: a longer context or a second application can push this into swapping.
- Q3_K_M is the only quantization that fits, and it is a heavily degraded one — expect noticeably worse output than the same model at Q4_K_M. A smaller model at Q4 is usually the better trade.
- 2 larger variants of Llama 3.2 Vision do not fit and would need CPU offload or different hardware.
RTX 4060 laptop limitations
- 8 GB VRAM limits you to 7–8B models at Q4 with a short context.
- System RAM is usually upgradeable on this class of laptop even though VRAM is not.
Recommended setup
Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving
How these numbers are calculated
- Memory need = quantized weights + KV cache at 8,192 tokens (f16) + 0.8 GB runtime overhead.
- 8 GB of VRAM on the NVIDIA GeForce RTX 4060 Laptop GPU at 256 GB/s.
- 16 GB of system RAM available for CPU offload when a model exceeds VRAM.
- Throughput is a memory-bandwidth roofline estimate, not a measurement. It is labelled "estimated" everywhere it appears.
- KV cache is computed from this model's published attention configuration.
FAQ
Can I run Llama 3.2 Vision on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM)?
Yes — Llama 3.2 Vision 11B at Q3_K_M needs about 6.7 GB of the 8 GB usable on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM) (~1.3 GB spare), at ~34.2 tok/s (estimated), with room for about 8,192 tokens of context.
Which quantization of Llama 3.2 Vision should I use on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM)?
Q3_K_M — it needs about 6.7 GB of the 8 GB available, downloads as roughly 4.5 GB, and runs at an estimated 34.2 tokens/sec with up to 8K of context.
What limits Llama 3.2 Vision on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM)?
Nothing binding — the model fits with headroom and generates at a usable speed on this hardware.
Which runtime should I use?
Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving
Other Computers
- Llama 3.2 Vision on MacBook Pro M4 Max 128 GB
- Llama 3.2 Vision on MacBook Pro M4 Max 48 GB
- Llama 3.2 Vision on MacBook Pro M4 Pro 24 GB
- Llama 3.2 Vision on MacBook Air M4 16 GB
Other Models on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM)
- MiniCPM-V on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM)
- Ministral on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM)
- Ministral 3 on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM)
- Mistral Family on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM)
- OLMo 2 on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM)
Llama 3.2 Vision on GPUs
- Llama 3.2 Vision on NVIDIA GeForce RTX 5070
- Llama 3.2 Vision on NVIDIA GeForce RTX 5060 Ti 8GB
- Llama 3.2 Vision on NVIDIA GeForce RTX 5060
- Llama 3.2 Vision on NVIDIA GeForce RTX 4070 Ti
What This Model Is Good At
Model & Tools
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