Written by Jakub Rusinowski · Last updated August 15, 2026
Yes, but it is tight
Yes, but it is tight — GPT-OSS 20B at Q2_K needs about 7.8 GB of the 8 GB usable on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM), leaving only ~0.2 GB before the runtime starts swapping. Expect ~28.2 tok/s (estimated), with room for about 8,192 tokens of context.
Confidence: medium · Recommended quantization: Q2_K · Estimated speed: ~28.2 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 | 41.2 GB | ✗ No | — | — | 40 GB |
| Q8_0 | 22.5 GB | ✗ No | — | — | 21.3 GB |
| Q6_K | 17.6 GB | ✗ No | — | — | 16.4 GB |
| Q5_K_M | 15.4 GB | ✗ No | — | — | 14.2 GB |
| Q4_K_M | 13.3 GB | ✗ No | — | — | 12.1 GB |
| Q3_K_M | 9.7 GB | ✗ No | — | — | 8.5 GB |
| Q2_K | 7.8 GB | ✓ Yes | 8K | ~28.2 tok/s | 6.6 GB |
| Variant | Needs at Q4_K_M | Fits? | Est. speed |
|---|---|---|---|
| GPT-oss 120B | 73.9 GB | ✗ Too large | — |
| GPT-OSS 20B | 13.3 GB | ✗ Too large | — |
Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving
Yes, but it is tight — GPT-OSS 20B at Q2_K needs about 7.8 GB of the 8 GB usable on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM), leaving only ~0.2 GB before the runtime starts swapping. Expect ~28.2 tok/s (estimated), with room for about 8,192 tokens of context.
Q2_K — it needs about 7.8 GB of the 8 GB available, downloads as roughly 6.6 GB, and runs at an estimated 28.2 tokens/sec with up to 8K 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