Best Local AI Models for Mac Studio
Mac Studio is the workstation for local AI. The 2026 M5 Ultra generation doubles down: up to 512GB of unified memory at 1.2 TB/s memory bandwidth, enough to run 120B-class MoE models and 70B dense models entirely in memory at production speeds. M5 Max configs (36-128GB) cover the 27B-70B sweet spot.
On a Mac Studio, the best local LLM ranges from Gemma 4 26B-A4B at 32GB to Llama 4 Maverick at 512GB. That spans 32GB to 512GB configurations, where 105 of ModelFit's 106 local models fit comfortably at the top tier. Pick your exact chip below for its ranked list.
Sizing rule: a local model needs about 0.6 GB of unified memory per billion parameters at Q4, and ModelFit budgets roughly 70% of each configuration's RAM. At 32GB the best fit is Gemma 4 26B-A4B (~16GB); at 512GB it is Llama 4 Maverick (~245GB), reaching an estimated 12 tok/s. Mid-range configurations trade model size for speed between those two points. What it will not run: dense models beyond the top tier's memory budget stay on a cloud API, and the 32GB tier caps out far earlier.
→ Pick your exact chip below for its ranked models and one-line install command.
Speeds are ModelFit estimates from chip bandwidth and model size, not measured benchmarks.
Cite this page: ModelFit, Best Local AI Models for Mac Studio, https://modelfit.io/mac-studio/, updated September 2026, CC BY 4.0.
Last updated: September 3, 2026 · Editor: ModelFit Team
Recommended Models
This model may feel memory-heavy on 64 GB RAM, but it is still listed for balanced speed and quality.
This model may feel memory-heavy on 64 GB RAM, but it is still listed for balanced speed and quality.
Best for reasoning, coding, agents. Strong fit for 64 GB RAM with balanced speed and quality.
Best for reasoning, coding, agent scenarios. Strong fit for 64 GB RAM with balanced speed and quality.
Best for chat, coding, multimodal. Strong fit for 64 GB RAM with balanced speed and quality.
Best for coding, agent, vision, long context. Strong fit for 64 GB RAM with balanced speed and quality.
Best for chat, coding, complex reasoning. Strong fit for 64 GB RAM with balanced speed and quality.
Best for coding, quality, long context. Strong fit for 64 GB RAM with balanced speed and quality.
Context costs memory too. Qwen3.6 35B-A3B (Q8) loads ~38.7 GB of weights; at 16k context the KV cache adds ~0.3 GB (still fits the ~48 GB usable RAM), and at 64k it adds ~1.3 GB (still fits).
KV-cache figures assume an fp16 cache, the llama.cpp/Ollama default. Standard GQA models use a size-class estimate (8 KV heads x 128 head dim class); hybrid linear-attention models (Qwen3.5/3.6, Qwen3-Next) use the exact per-token cost from their published config, since only their sparse full-attention layers cache KV. A q8_0 KV cache roughly halves either figure. Estimates, not measurements.
Pick Your Exact Mac Studio Chip
Where to Buy for Local AI
best configsComfortably runs 70B models at usable speed, the value pick for serious local AI.
Check price on AmazonFrontierHeadroom for the largest open-weight models (Llama 4 Scout, big MoE) at home.
Check price on AmazonPrefer to buy direct? Buy from Apple (same price, no affiliate link).
Archive your model library off the internal drive. Quantized models run 5 to 40GB each, so 2TB holds dozens with room to spare.
Check price on Amazon40Gbps external storage fast enough to run models from. Pair it with an M.2 drive for a portable model vault.
Check price on AmazonMore ports for the external drives, displays and peripherals around a local-AI workstation.
Check price on AmazonModelFit may earn a commission on purchases through these links, at no extra cost to you.
Need a Model Bigger Than This Mac Studio Runs?
by the hour70B-class and frontier open-weight models that won't fit in unified memory run great on an hourly rented GPU, same open weights, same Ollama workflow, no subscription.
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Frequently Asked Questions
What is the best AI model for Mac Studio?
Mac Studio is the workstation for local AI. The 2026 M5 Ultra generation doubles down: up to 512GB of unified memory at 1.2 TB/s memory bandwidth, enough to run 120B-class MoE models and 70B dense models entirely in memory at production speeds. M5 Max configs (36-128GB) cover the 27B-70B sweet spot. On the default Apple M5 Max with 64GB RAM, Qwen3.6 35B-A3B (Q8) is our top pick, handling models up to about 35B parameters at this RAM. Higher-RAM Mac Studio configurations, including Pro and Max tiers where available, reach into the 70B-120B+ parameter range.
What size models fit on Mac Studio?
With 64GB unified memory, Mac Studio runs models up to about 35B parameters comfortably. Strong picks include Qwen3.6 35B-A3B (Q8), Qwen3.5 35B-A3B Instruct (Q8), Qwen3.6 35B-A3B. Higher-RAM configurations, including Pro and Max tiers where available, reach into the 70B-120B+ parameter range. Use the ModelFit wizard to match your exact RAM and chip.
How fast is local AI on Mac Studio?
Expect an estimated 38 tokens per second on the Apple M5 Max with optimized, quantized models. The Mac Studio M5 Ultra (2026) restores the big-memory Mac: 512GB unified memory at 1.2 TB/s bandwidth, roughly 50% above the M3 Ultra. In ModelFit estimates that is ~135 tok/s on a 7B Q4 reference and comfortable speeds on 120B-class MoE models like gpt-oss-120b, entirely in memory. Pre-orders opened 2026-08-26, shipping September 22. (Speeds are ModelFit estimates, not measured benchmarks, and vary with model size and quantization.)