text model · Ornith · macOS
Can I run Ornith 1.5 35B-A3B on Apple M5 Pro (48GB)?
Yes. Ornith 1.5 35B-A3B runs on Apple M5 Pro (48GB) at Q4_K_M (~22.4 GB of ~32 GB usable).
Runs at Q4_K_M using ~22.4 GB of ~32 GB usable.
That figure is at a 4k context and moves about ±15% as context length changes. Apple M5 Pro (48GB) leaves ~9.6 GB of headroom.
- Q4_K_M needed
- ~22.4 GB
- Usable on device
- ~32 GB
- Device memory
- 48 GB
- Best quant
- Q4_K_M
Which quant fits
Run it
Pick your tool. All 3 load the same Q4_K_M weights.
ollama run ornith-1.5:35b llama-cli -hf ornith-ai/Ornith-1.5-35B-A3B-GGUF:Q4_K_M lms get ornith-ai/Ornith-1.5-35B-A3B-GGUF - Parameters
- 35B (MoE, 3B active)
- Q4_K_M size
- 20.22 GB
- Q8_0 size
- 35.21 GB
- Context
- 256k
- Ollama tag
- ornith-1.5:35b
- Memory
- 48 GB unified
- Usable for weights
- ~32 GB
- Best runtime
- MLX direct / Ollama (MLX backend)
You could also run
Run Ornith 1.5 35B-A3B on other hardware
FAQ
Can Apple M5 Pro (48GB) run Ornith 1.5 35B-A3B?
Yes. Ornith 1.5 35B-A3B runs on Apple M5 Pro (48GB) at Q4_K_M (~22.4 GB of ~32 GB usable).
How much memory does Ornith 1.5 35B-A3B need?
Apple M5 Pro (48GB) has room to spare. At Q4_K_M the weights are ~20.22 GB; with KV cache and runtime overhead, budget ~22.4 GB at a 4k context. It is a Mixture-of-Experts model (35B total / 3B active), so all experts must stay in memory; memory tracks total params, not active params.
What is the best tool to run Ornith 1.5 35B-A3B 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.
Embed this
A live badge for your model card or README, updated as the data is. [](https://localmodel.run/can-i-run/ornith-1.5-35b-a3b/apple-m5-pro-48gb) 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.