text model · Laguna · macOS
Can I run Laguna XS 2.1 on Apple M3 Ultra (256GB)?
Yes. Laguna XS 2.1 runs on Apple M3 Ultra (256GB) at Q4_K_M (~22.2 GB of ~192 GB usable).
Runs at Q4_K_M using ~22.2 GB of ~192 GB usable. You have room for FP16 for higher quality.
That figure is at a 4k context and moves about ±15% as context length changes. Apple M3 Ultra (256GB) leaves ~169.8 GB of headroom, room to step up to FP16 for higher quality.
- Q4_K_M needed
- ~22.2 GB
- Usable on device
- ~192 GB
- Device memory
- 256 GB
- Best quant
- Q4_K_M
Which quant fits
Run it
Loads the Q4_K_M weights.
ollama run laguna-xs-2.1 - Parameters
- 33.4B (MoE, 3B active)
- Q4_K_M size
- 20 GB
- Q8_0 size
- 36 GB
- Context
- 256k
- Ollama tag
- laguna-xs-2.1
- Memory
- 256 GB unified
- Usable for weights
- ~192 GB
- Power draw
- ~270 W
- Best runtime
- MLX direct / Ollama (MLX backend)
You could also run
Run Laguna XS 2.1 on other hardware
FAQ
Can Apple M3 Ultra (256GB) run Laguna XS 2.1?
Yes. Laguna XS 2.1 runs on Apple M3 Ultra (256GB) at Q4_K_M (~22.2 GB of ~192 GB usable).
How much memory does Laguna XS 2.1 need?
Apple M3 Ultra (256GB) has room to spare. At Q4_K_M the weights are ~20 GB; with KV cache and runtime overhead, budget ~22.2 GB at a 4k context. It is a Mixture-of-Experts model (33.4B total / 3B active), so all experts must stay in memory; memory tracks total params, not active params.
What is the best tool to run Laguna XS 2.1 on macOS?
LM Studio for a simple setup; mlx-lm for the most speed. vLLM is NOT a Mac tool, it is a CUDA/Linux serving engine. Unified memory is not a fixed VRAM slice; ~70% is usable for weights.
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A live badge for your model card or README, updated as the data is. [](https://localmodel.run/can-i-run/laguna-xs-2.1/apple-m3-ultra-256gb) Sources
Weights are measured from GGUF files; KV cache and overhead are computed, so totals can vary ~15% with context and runtime. Any tok/s is a bandwidth estimate. See methodology.