Best LLM for Mac (Apple Silicon) in 2026

Gemma 4 is Google's first-class Mac deployment model, with mature MLX support across all variants from e2b (~1.5GB) to the 31B dense flagship (~18GB at Q4). The new Apache 2.0 license eliminates the commercial restrictions that limited prior Gemma generations. For most Mac users — from 16GB MacBook Air to 64GB MacBook Pro — Gemma 4 hits the sweet spot of capability, native multimodal support, and resource efficiency. The e4b variant in particular runs comfortably on entry-tier Macs while delivering useful chat and reasoning capability.

Qwen 3.6's dense 27B variant fits comfortably on a 32GB+ Mac at Q4_K_M (approximately 16GB). For users with 64GB+ Macs (MacBook Pro M4 Max, Mac Studio), it's the strongest single-deployable open-weight reasoning model. Apache 2.0 licensing, broad multilingual support, and native Qwen-Agent integration make Qwen 3.6 a compelling choice for Mac users wanting frontier capability without committing to multi-GPU server deployment. The 35B-A3B MoE variant is also viable on 64GB+ Macs and runs at small-model speeds.

Mistral Small 4's 6B active parameter MoE architecture is well-suited to Apple Silicon's unified memory architecture — the 119B total parameter footprint at Q4_K_M (approximately 65GB) fits on Mac Studio M2/M3/M4 Ultra configurations with 96GB+ unified memory. Active parameter count of 6B means inference runs at fast 6B-class speeds. For European Mac users or any Mac deployment where Apache 2.0 licensing and EU data sovereignty matter, Mistral Small 4 is a particularly strong choice.

Llama 3 is the workhorse for Mac LLM deployment — a 2024-vintage model with years of MLX optimization, community fine-tunes, and deployment guides. The 8B variant at Q4_K_M (approximately 4.5GB) runs comfortably on any 16GB+ Mac. The 70B variant at Q4_K_M (approximately 40GB) fits on 64GB+ Macs. While Llama 3 doesn't match newer 2026 flagships on absolute capability, the maturity of the Mac deployment ecosystem makes it the lowest-friction path to a working local Mac LLM for most users.

Microsoft's Phi-4 (14B dense) at Q4_K_M (approximately 8.5GB) fits comfortably on 16GB+ Macs and delivers exceptional capability per parameter. MIT licensing makes it commercially deployable without restrictions. For Mac users wanting strong reasoning capability — particularly on math and code tasks — without committing to a 27B-70B class model, Phi-4 hits a productive sweet spot. The Phi-4-multimodal variant (5.6B) extends the family to vision-and-speech use cases on smaller Macs.