Written by Jakub Rusinowski · Last updated August 15, 2026
Yes, but it is tight
Yes, but it is tight — Laguna XS 2.1 33B-A3B at Q4_K_M needs about 22.6 GB of the 24 GB usable on RTX 4090 Desktop (24 GB VRAM, 64 GB RAM), leaving only ~1.4 GB before the runtime starts swapping. Expect ~170.6 tok/s (estimated), with room for about 8,192 tokens of context.
Confidence: low · Recommended quantization: Q4_K_M · Estimated speed: ~170.6 tok/s
| Usable memory for models | 24 GB |
| Memory bandwidth | 1008 GB/s |
| Form factor | Desktop |
| Operating system | Windows or Linux |
| Memory upgradeable | Yes |
| Quant | Memory needed | Fits 24 GB? | Max context | Est. speed | Download |
|---|---|---|---|---|---|
| F16 | 68.6 GB | ✗ No | — | — | 66 GB |
| Q8_0 | 37.7 GB | ✗ No | — | — | 35.1 GB |
| Q6_K | 29.7 GB | ✗ No | — | — | 27.1 GB |
| Q5_K_M | 26 GB | ✗ No | — | — | 23.4 GB |
| Q4_K_M | 22.6 GB | ✓ Yes | 8K | ~170.6 tok/s | 19.9 GB |
| Q3_K_M | 16.7 GB | ✓ Yes | 32K | ~193.9 tok/s | 14.1 GB |
| Q2_K | 13.5 GB | ✓ Yes | 32K | ~209.6 tok/s | 10.8 GB |
Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving
Yes, but it is tight — Laguna XS 2.1 33B-A3B at Q4_K_M needs about 22.6 GB of the 24 GB usable on RTX 4090 Desktop (24 GB VRAM, 64 GB RAM), leaving only ~1.4 GB before the runtime starts swapping. Expect ~170.6 tok/s (estimated), with room for about 8,192 tokens of context.
Q4_K_M — it needs about 22.6 GB of the 24 GB available, downloads as roughly 19.9 GB, and runs at an estimated 170.6 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
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