text model · Ornith · macOS

Can I run Ornith 1.0 35B on Apple M4 Max (128GB)?

Compatibility verdict VRAM threshold engine

Yes, it runs GPU accelerated

Yes. Ornith 1.0 35B runs on Apple M4 Max (128GB) at Q4_K_M (~23.2 GB of ~96 GB usable).

Needs ~23.2 GB Device usable ~96 GB

Runs at Q4_K_M using ~23.2 GB of ~96 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 M4 Max (128GB) leaves ~72.8 GB of headroom, room to step up to FP16 for higher quality.

Q4_K_M needed: ~23.2 GB
Usable on device: ~96 GB
Device memory: 128 GB
Best quant: Q4_K_M

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Which quant fits

Quant ladder vs ~96 GB usable

Q2_K

~16.9 GB

Q3_K_M

~19.3 GB

Q4_K_M

~23.2 GB

Q5_K_M

~27.1 GB

Q6_K

~30.9 GB

Q8_0

~39.2 GB

FP16

~71.2 GB

The line marks Apple M4 Max (128GB)'s ~96 GB budget; rungs past it are too large.

Run it

Install commands macOS

Pick your tool. All 3 load the same Q4_K_M weights.

Ollama

$ ollama run ornith:35b

llama.cpp

$ llama-cli -hf deepreinforce-ai/Ornith-1.0-35B-GGUF:Q4_K_M

LM Studio

$ lms get deepreinforce-ai/Ornith-1.0-35B-GGUF

Model Ornith

Parameters: 35B (MoE, 3B active)
Q4_K_M size: 21 GB
Q8_0 size: 37 GB
Context: 256k
Ollama tag: ornith:35b

Full Ornith 1.0 35B requirements →

Device macOS

Memory: 128 GB unified
Usable for weights: ~96 GB
Power draw: ~145 W
Best runtime: MLX direct / Ollama (MLX backend)

Best models for Apple M4 Max (128GB) →

You could also run

Run Ornith 1.0 35B on other hardware

Nvidia GeForce RTX 5090 (32GB)32GB RAM Laptop (CPU/iGPU only)Apple M4 Pro (48GB)Apple M5 Pro (48GB)Apple M4 Max (64GB)AMD Ryzen AI Halo (128GB)

FAQ

Can Apple M4 Max (128GB) run Ornith 1.0 35B?

Yes. Ornith 1.0 35B runs on Apple M4 Max (128GB) at Q4_K_M (~23.2 GB of ~96 GB usable).

How much memory does Ornith 1.0 35B need?

Apple M4 Max (128GB) has room to spare. At Q4_K_M the weights are ~21 GB; with KV cache and runtime overhead, budget ~23.2 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 1.0 35B 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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Markdown

[![Ornith 1.0 35B on Apple M4 Max (128GB)](https://localmodel.run/badge/ornith-1.0-35b/apple-m4-max-128gb.svg)](https://localmodel.run/can-i-run/ornith-1.0-35b/apple-m4-max-128gb)

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.