Best local LLM for Mac Silicon
Last updated 2026-05-26 · Page updated 2026-07-13
Top 8 open-source picks for Apple Silicon Macs, ranked by benchmark performance and real-world fit. Updated monthly.
Qwen 3 30B-A3B
Alibaba's Qwen 3 MoE with 30B total and just 3B active parameters, supporting hybrid thinking mode. MMLU 81.4, AIME24 80.4, 100+ languages, Apache 2.0.
Granite 4.0 H-Small 32B-A9B
IBM's hybrid Mamba-2 + MoE model with 32B total and 9B active parameters, engineered to slash long-context memory use by roughly 70% versus comparable transformers under Apache 2.0.
gpt-oss 20B
OpenAI's compact open-weight MoE with 3.6B active out of 21B total parameters. Matches o3-mini on a laptop-class GPU under Apache 2.0.
Qwen 3 VL 30B-A3B
Qwen 3 VL's sweet spot: a 30B MoE with 3B active parameters and 256k context. Delivers most of the 235B's quality at a fraction of the hardware cost.
ERNIE 4.5 21B-A3B Thinking
Baidu's compact reasoning MoE with 3B active parameters out of 21B total. Fast inference thanks to the small active set, with Chinese-language strength.
Trinity Mini 26B-A3B
Arcee AI's US-built MoE with 3B active parameters out of 26B total. Apache-licensed, fast in practice, and tuned for agent-style workloads.
Kanana 2 30B-A3B Thinking
Kakao's agentic 30B MoE (3B active) with native hybrid thinking and Korean-first training. Apache 2.0 with MLA attention and 131k context.
Qwen 3 Omni 30B-A3B
Alibaba's omni-modal 30B MoE (3B active) with streaming speech, 119-language ASR, and Apache 2.0 licensing. The most accessible truly omnimodal open model.
Which GPU should you buy to run Qwen 3 30B-A3B?
To run Qwen 3 30B-A3B locally at Q4, you need ~19 GB of VRAM. The best value for this is a RTX 4090 (24 GB VRAM).
As an Amazon Associate, BestLLMfor earns from qualifying purchases, at no extra cost to you. It does not influence our independent rankings.
Frequently asked questions
What is the best local LLM for Apple Silicon Macs?
Qwen 3 30B-A3B tops this ranking — a 30B model, licensed under Apache 2.0, needing about 19 GB of VRAM at Q4 quantization. See the full list below for the runner-ups and how they compare.
How much VRAM do I need to run Qwen 3 30B-A3B?
At Q4 quantization, Qwen 3 30B-A3B needs about 19 GB of VRAM and fits comfortably on a single 24 GB GPU.
Which of these models fit an 16 GB GPU?
At Q4 quantization, gpt-oss 20B, ERNIE 4.5 21B-A3B Thinking, Trinity Mini 26B-A3B fit within 16 GB of VRAM.
Are the models on this Apple Silicon Macs list free for commercial use?
Licenses across this list include Apache 2.0. Check the specific license of each model on its catalog page before deploying commercially, as terms vary by author.
What context window do these models support?
Context windows on this list range from 125k to 256k tokens, depending on the model.