text model · Laguna · macOS
Can I run Laguna S 2.1 on Apple M5 (16GB)?
No. Laguna S 2.1 needs ~92.8 GB even at Q4_K_M, but Apple M5 (16GB) only has ~10.5 GB usable.
Needs ~92.8 GB even at Q4_K_M, but only ~10.5 GB is usable.
That figure is at a 4k context and moves about ±15% as context length changes.
The gap is about 82.3 GB: Laguna S 2.1 needs roughly 92.8 GB at Q4_K_M and Apple M5 (16GB) leaves only about 10.5 GB usable for a model. The lightest tracked hardware that runs Laguna S 2.1 is the Apple M4 Max (128GB) at 128 GB. See Laguna S 2.1 on Apple M4 Max (128GB).
- Q4_K_M needed
- ~92.8 GB
- Usable on device
- ~10.5 GB
- Device memory
- 16 GB
Which quant fits
- Parameters
- 118B (MoE, 8B active)
- Q4_K_M size
- 89.44 GB
- Q8_0 size
- 119.91 GB
- Context
- 1000k
- Ollama tag
- laguna-s-2.1:latest
- Memory
- 16 GB unified
- Usable for weights
- ~10.5 GB
- Best runtime
- MLX direct / Ollama (MLX backend)
What you can run instead
Run Laguna S 2.1 on other hardware
FAQ
Can Apple M5 (16GB) run Laguna S 2.1?
No. Laguna S 2.1 needs ~92.8 GB even at Q4_K_M, but Apple M5 (16GB) only has ~10.5 GB usable.
How much memory does Laguna S 2.1 need?
Apple M5 (16GB) does not have enough memory. At Q4_K_M the weights are ~89.44 GB; with KV cache and runtime overhead, budget ~92.8 GB at a 4k context. It is a Mixture-of-Experts model (118B total / 8B active), so all experts must stay in memory; memory tracks total params, not active params.
What is the best tool to run Laguna S 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-s-2.1/apple-m5-16gb) 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.