Written by Jakub Rusinowski · Last updated June 26, 2026
Yes, but it is tight
Yes, but it is tight — GLM-6 9B at Q4_K_M needs about 7.4 GB of the 8 GB usable on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM), leaving only ~0.6 GB before the runtime starts swapping. Expect ~31.4 tok/s (estimated), with room for about 8,192 tokens of context.
Confidence: low · Recommended quantization: Q4_K_M · Estimated speed: ~31.4 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 | 20 GB | ✗ No | — | — | 18 GB |
| Q8_0 | 11.6 GB | ✗ No | — | — | 9.6 GB |
| Q6_K | 9.4 GB | ✗ No | — | — | 7.4 GB |
| Q5_K_M | 8.4 GB | ✗ No | — | — | 6.4 GB |
| Q4_K_M | 7.4 GB | ✓ Yes | 8K | ~31.4 tok/s | 5.4 GB |
| Q3_K_M | 5.8 GB | ✓ Yes | 16K | ~41.6 tok/s | 3.8 GB |
| Q2_K | 5 GB | ✓ Yes | 16K | ~50.7 tok/s | 3 GB |
| Variant | Needs at Q4_K_M | Fits? | Est. speed |
|---|---|---|---|
| GLM-6 355B-A32B | 219.2 GB | ✗ Too large | — |
| GLM-6 9B | 7.4 GB | ✓ Fits | ~31.4 tok/s |
Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving
Yes, but it is tight — GLM-6 9B at Q4_K_M needs about 7.4 GB of the 8 GB usable on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM), leaving only ~0.6 GB before the runtime starts swapping. Expect ~31.4 tok/s (estimated), with room for about 8,192 tokens of context.
Q4_K_M — it needs about 7.4 GB of the 8 GB available, downloads as roughly 5.4 GB, and runs at an estimated 31.4 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