Written by Jakub Rusinowski · Last updated August 15, 2026
Yes — comfortably
Yes, comfortably — Llama 3.2 3B Instruct at Q8_0 needs about 5.2 GB of the 8 GB usable on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM), leaving ~2.8 GB spare and running at ~47 tok/s (estimated), with room for about 32,768 tokens of context.
Confidence: high · Recommended quantization: Q8_0 · Estimated speed: ~47 tok/s
| Usable memory for models | 8 GB |
| Memory bandwidth | 272 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) |
| Quant | Memory needed | Fits 8 GB? | Max context | Est. speed | Download |
|---|---|---|---|---|---|
| F16 | 8.2 GB | ✗ No | — | — | 6.4 GB |
| Q8_0 | 5.2 GB | ✓ Yes | 32K | ~47 tok/s | 3.4 GB |
| Q6_K | 4.4 GB | ✓ Yes | 32K | ~57.3 tok/s | 2.6 GB |
| Q5_K_M | 4 GB | ✓ Yes | 32K | ~63.7 tok/s | 2.3 GB |
| Q4_K_M | 3.7 GB | ✓ Yes | 32K | ~71.2 tok/s | 1.9 GB |
| Q3_K_M | 3.1 GB | ✓ Yes | 32K | ~88.8 tok/s | 1.4 GB |
| Q2_K | 2.8 GB | ✓ Yes | 32K | ~102.9 tok/s | 1.1 GB |
| Variant | Needs at Q4_K_M | Fits? | Est. speed |
|---|---|---|---|
| Llama 3.2 90B Vision Instruct | 57.8 GB | ✗ Too large | — |
| Llama 3.2 11B Vision Instruct | 8.5 GB | ✗ Too large | — |
| Llama 3.2 3B Instruct | 3.7 GB | ✓ Fits | ~71.2 tok/s |
| Llama 3.2 1B Instruct | 1.8 GB | ✓ Fits | ~152.1 tok/s |
Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving
Yes, comfortably — Llama 3.2 3B Instruct at Q8_0 needs about 5.2 GB of the 8 GB usable on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM), leaving ~2.8 GB spare and running at ~47 tok/s (estimated), with room for about 32,768 tokens of context.
Q8_0 — it needs about 5.2 GB of the 8 GB available, downloads as roughly 3.4 GB, and runs at an estimated 47 tokens/sec with up to 32K of context.
Nothing binding — the model fits with headroom and generates at a usable speed on this hardware.
Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving
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