Best Local AI Models for Apple Silicon / Mac
Apple Silicon's unified memory earns its keep on the mid-to-large models that strain a single consumer GPU. These need 16 to 48 GB at Q4 — exactly the range where a Mac's shared memory pool beats building a dual-GPU rig.
Llama 3.3 70B
Meta · Llama 3.3 Community
Meta's flagship open-weight model and the go-to choice for users who want GPT-4-class performance without sending data to the cloud. Consistently tops open-source leaderboards. Needs ~48 GB VRAM at Q4_K_M — a dual-GPU rig or Apple Silicon with 48 GB unified memory.
Min VRAM
48 GB
Context
128K
Run with Ollama
ollama run llama3.3:70bMixtral 8x7B
Mistral AI · Apache 2.0
A sparse mixture-of-experts model that activates only 12B parameters per token while carrying 47B total, delivering 70B-class results at a fraction of the compute cost. One of the best open-weight models available under a fully permissive license.
Min VRAM
26 GB
Context
32K
Run with Ollama
ollama run mixtral:8x7bOrnith 1.0 35B
DeepReinforce · MIT
Scores 75.6% on SWE-bench Verified — one of the highest results for any open-weight coding model and above most paid assistants. From the lab DeepReinforce, trained with RL self-improvement for terminal control and tool calling. MIT licensed, 262K context. There is no Ollama library tag yet — pull the GGUF directly with ollama run hf.co/deepreinforce-ai/Ornith-1.0-35B-GGUF.
Min VRAM
20 GB
Context
262K
Run with Ollama
ollama run hf.co/deepreinforce-ai/Ornith-1.0-35B-GGUFWant to mix in more filters?
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