Best local LLM for mac 128gb
Last updated 2026-05-26 · Page updated 2026-07-13
Top 8 open-source picks for mac 128gb, 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.
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.
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.
Apertus 70B
A Swiss AI joint effort (EPFL, ETH, CSCS) trained on 15T tokens covering 1000+ languages, including Swiss German and Romansh. Apache 2.0.
Nemotron Nano 3 30B-A3B
NVIDIA's Mamba-2 + Transformer hybrid MoE with 3B active out of 30B total parameters. A native 1M-token context with roughly 4× the throughput of Nemotron 2.
Nemotron 3 Nano Omni 30B-A3B
NVIDIA's omnimodal MoE: 30B total / 3B active, handling text, image, audio, and video in 256k context. Hybrid Mamba2-MoE architecture delivers 9x the throughput of competing open omni models. Released April 2026.
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).
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Frequently asked questions
What is the best local LLM for mac 128gb?
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 24 GB GPU?
At Q4 quantization, Qwen 3 30B-A3B, Granite 4.0 H-Small 32B-A9B, Qwen 3 VL 30B-A3B, Kanana 2 30B-A3B Thinking, Qwen 3 Omni 30B-A3B and 2 more fit within 24 GB of VRAM.
Are the models on this mac 128gb list free for commercial use?
Licenses across this list include Apache 2.0, NVIDIA Open Model License. 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 64k to 976k tokens, depending on the model.