aicanrun

AI Models for Mac mini M6 — What runs on 16GB

54 great · 35 won't fit
Compact silver Mac mini held in one hand
Chip
Apple M6
Memory bandwidth
170 GB/s
Unified memory
16 GB
Usable for models
~13 GB
Cooling
Active
Year
2026

Specs checked against manufacturer and public documentation on . Results below are estimates, not measurements.

What runs on the Mac mini M6

All 89 models use the recommended quant when it fits, or the largest smaller tracked fallback for this 16GB configuration. Select any row for the full report and step-by-step setup guide.

ModelParamsQuantNeedsSpeedVerdict
Bonsai 27B (1-bit)27BQ1_05GB~22.4–31.3 tokens/s✓ Runs great
Ternary Bonsai 27B27BQ2_08.6GB~11.8–16.5 tokens/s✓ Runs great
Qwen3 14B14.8BQ4_K_M11.3GB~9.4–13.2 tokens/s✓ Runs great
Phi-4 14B14.7BQ4_K_M11.4GB~9.3–13.1 tokens/s✓ Runs great
Ministral 3 14B14BQ4_K_M10.4GB~10.4–14.5 tokens/s✓ Runs great
Gemma 3 12B12.2BQ4_K_M9.3GB~11.6–16.3 tokens/s✓ Runs great
Gemma 4 12B12BQ4_09GB~12.1–17 tokens/s✓ Runs great
Grug 12B12BQ4_K_M9.7GB~11–15.5 tokens/s✓ Runs great
GRM 3.2 Cliff 9B9.4BQ4_K_M7.7GB~14.4–20.2 tokens/s✓ Runs great
grug 9B (ProCreations)9.4BQ4_K_M7.7GB~14.4–20.2 tokens/s✓ Runs great
Fara 1.5 9B9.4BQ4_K_M7.7GB~14.4–20.2 tokens/s✓ Runs great
Qwen 3.5 9B9BQ4_K_M7.4GB~14.9–20.9 tokens/s✓ Runs great
Ornith 1.0 9B9BQ4_K_M7.3GB~15.2–21.3 tokens/s✓ Runs great
Qwythos 9B v29BQ4_K_M7.4GB~14.9–20.9 tokens/s✓ Runs great
UI-Mate 9B9BQ4_K_M7.6GB~14.4–20.2 tokens/s✓ Runs great
Tini Cybersec 8B-A1B8.5BQ4_K_M6.9GB~138.9–194.5 tokens/s✓ Runs great
Qwen3 8B8.2BQ4_K_M6.6GB~17–23.8 tokens/s✓ Runs great
Llama 3.1 8B8BQ4_K_M6.5GB~17.3–24.3 tokens/s✓ Runs great
Ministral 8B8BQ4_K_M6.5GB~17.3–24.3 tokens/s✓ Runs great
Ternary Bonsai 8B8BQ2_03.7GB~38.6–54.1 tokens/s✓ Runs great
Ministral 3 8B8BQ4_K_M6.8GB~16.3–22.9 tokens/s✓ Runs great
LFM2.5 8B-A1B8BQ4_K_M6.8GB~130.8–183.1 tokens/s✓ Runs great
Granite 4.2 8B8BQ4_K_M6.9GB~16–22.5 tokens/s✓ Runs great
Ling 3.0 Tiny7.9BQ4_K_M6.5GB~97.9–137 tokens/s✓ Runs great
DeepSeek R1 Distill 7B7.6BQ4_K_M6.3GB~18.1–25.3 tokens/s✓ Runs great
Mistral 7B v0.37.2BQ4_K_M5.9GB~19.3–27 tokens/s✓ Runs great
AREX Turbo 4B4.5BQ4_K_M4.2GB~29.3–41 tokens/s✓ Runs great
Fara 1.5 4B4.5BQ4_K_M4.2GB~29.3–41 tokens/s✓ Runs great
Gemma 3 4B4.3BQ4_K_M3.7GB~34–47.6 tokens/s✓ Runs great
Nanbeige 4.2 3B4.2BQ4_K_M3.9GB~31.5–44.1 tokens/s✓ Runs great
Qwen3 4B4BQ4_K_M3.7GB~34–47.6 tokens/s✓ Runs great
Qwen 3.5 4B4BQ4_K_M3.9GB~31.5–44.1 tokens/s✓ Runs great
Gemma 4 E4B4BQ4_K_M6.3GB~17–23.8 tokens/s✓ Runs great
Ternary Bonsai 4B4BQ2_02.2GB~77.3–108.2 tokens/s✓ Runs great
Nemotron 3 Nano 4B4BQ4_K_M4GB~30.4–42.5 tokens/s✓ Runs great
Agents-A1 4B4BQ4_K_M3.9GB~31.5–44.1 tokens/s✓ Runs great
Phi-4 Mini 3.8B3.8BQ4_K_M3.7GB~34–47.6 tokens/s✓ Runs great
Llama 3.2 3B3.2BQ4_K_M3.1GB~42.5–59.5 tokens/s✓ Runs great
SmolLM3 3B3.1BQ4_K_M3GB~44.7–62.6 tokens/s✓ Runs great
LFM2.5-VL 3B3.1BQ4_K_M2.8GB~50–70 tokens/s✓ Runs great
Ministral 3 3B3BQ4_K_M3.2GB~40.5–56.7 tokens/s✓ Runs great
G9v3 3B3BQ4_K_M3GB~44.7–62.6 tokens/s✓ Runs great
Granite 4.2 3B3BQ4_K_M3.3GB~38.6–54.1 tokens/s✓ Runs great
LFM2.5 2.6B2.7BQ4_K_M2.8GB~50–70 tokens/s✓ Runs great
Qwen 3.5 2B2BQ4_K_M2.3GB~65.4–91.5 tokens/s✓ Runs great
Gemma 4 E2B2BQ4_K_M4.2GB~27.4–38.4 tokens/s✓ Runs great
DeepSeek R1 Distill 1.5B1.8BQ4_K_M2.1GB~77.3–108.2 tokens/s✓ Runs great
Qwen3 1.7B1.7BQ8_02.8GB~47.2–66.1 tokens/s✓ Runs great
SmolLM2 1.7B1.7BQ4_K_M2.1GB~77.3–108.2 tokens/s✓ Runs great
Ternary Bonsai 1.7B1.7BQ2_01.4GB~170–238 tokens/s✓ Runs great
Llama 3.2 1B1.2BQ4_K_M1.7GB~106.3–148.7 tokens/s✓ Runs great
Gemma 3 1B1BQ4_K_M1.7GB~106.3–148.7 tokens/s✓ Runs great
OvisOCR2 0.8B0.8BQ4_K_M1.5GB~141.7–198.3 tokens/s✓ Runs great
Qwen3 0.6B0.6BQ8_01.5GB~141.7–198.3 tokens/s✓ Runs great
Qwen3.8 2.4T-A95B2400BIQ4_XS1377.6GB—✕ Won't fit
Inkling952.4BQ8_0967.1GB—✕ Won't fit
LongCat Flash Chat561.9BIQ1_S159.8GB—✕ Won't fit
Ornith 1.0 397B397BQ4_K_M285.8GB—✕ Won't fit
Hunyuan 3 (Hy3)298.8BQ4_K_M213GB—✕ Won't fit
DeepSeek V4 Flash 0731284BQ4_K_XL163.8GB—✕ Won't fit
Inkling Small276BQ4_K_M190.7GB—✕ Won't fit
Ling 3.0 Flash124BQ4_K_M82.5GB—✕ Won't fit
Laguna S 2.1118BQ4_K_M109.9GB—✕ Won't fit
GLM-4.5V106BQ4_K_M75GB—✕ Won't fit
GLM-4.5-Air106BQ4_K_M75GB—✕ Won't fit
Llama 3.3 70B70BQ4_K_M50.3GB—✕ Won't fit
BigBang V1 36B-A3B36BQ4_K_M26.3GB—✕ Won't fit
Qwen 3.5 35B-A3B35BQ4_K_M26.4GB—✕ Won't fit
Qwen 3.6 35B-A3B35BQ4_K_M24.1GB—✕ Won't fit
Ornith 1.0 35B-A3B35BQ4_K_M25.5GB—✕ Won't fit
XYZ-Aquila mini 35B-A3B35BQ4_K_M25.7GB—✕ Won't fit
KAT-Coder V2.5 Dev35BQ4_K_M25.7GB—✕ Won't fit
Laguna XS 2.133BQ4_K_M24.4GB—✕ Won't fit
Qwen3 32B32.8BQ4_K_M23.9GB—✕ Won't fit
Nemotron 3 Nano Omni 30B-A3B31BQ4_K_M26.5GB—✕ Won't fit
Gemma 4 31B31BQ4_K_M22.2GB—✕ Won't fit
Qwen3 30B A3B30.5BQ4_K_M22.5GB—✕ Won't fit
Nemotron 3 Nano 30B-A3B30BQ4_K_M28.7GB—✕ Won't fit
Nemotron 3.5 Lightning 30B-A3B30BQ8_036.1GB—✕ Won't fit
Salience 1.5 Flash30BQ4_K_M22.5GB—✕ Won't fit
Granite 4.2 30B30BQ4_K_M21.5GB—✕ Won't fit
Muse Glimmer 30B29.6BK_QUANT_17GB20.5GB—✕ Won't fit
Qwen 3.5 27B27BQ4_K_M20.2GB—✕ Won't fit
Qwen 3.6 27B27BQ4_K_M18.7GB—✕ Won't fit
Fara 1.5 27B27BQ4_K_M21.1GB—✕ Won't fit
Qwen3.8 27B27BQ4_K_M21GB—✕ Won't fit
UI-Mate 27B27BQ4_K_M21.1GB—✕ Won't fit
Gemma 4 26B-A4B26BQ4_017.7GB—✕ Won't fit
GPT-OSS 20B21BMXFP415GB—✕ Won't fit

~ = bandwidth-based estimate · open a row to see the recommended app and exact steps

Other Mac mini M6 memory options

Check 24GBCheck 32GB

FAQ

What is the biggest local AI model the Mac mini M6 · 16GB can run?

Ternary Bonsai 27B is the largest model in our 89-model comparison that fits at Q2_0. It needs about 8.6GB inside our 13GB working-memory budget, with an estimated 11.8–16.5 tokens/s decode range.

How much of the 16GB unified memory is available to a local LLM?

We use a conservative 13GB working budget, leaving room for macOS, the inference app, and normal background activity. Memory pressure, context length, and other open apps can change the real limit.

Can the Mac mini M6 · 16GB run Llama 3.1 8B?

Yes. At Q4_K_M, our estimate uses 6.5GB and lands around 17.3–24.3 tokens/s.

Can the Mac mini M6 · 16GB run Qwen 3.6 27B?

Not at the recommended Q4_K_M quant. It needs about 18.7GB in this 4K-context estimate.

Can the Mac mini M6 · 16GB run DeepSeek V4 Flash 0731?

No tracked quant fits our conservative 13GB working-memory budget. The recommended Q4_K_XL alone needs about 163.8GB at 4K context.

Which app should I use for local AI on the Mac mini M6?

For most exact GGUF repositories and quants on this site, start with LM Studio's graphical Discover, download, load, and chat flow. Jan is the open-source GGUF alternative; Ollama is strongest when the exact model already has a trustworthy catalog package or you want coding/API integrations; Msty is useful for mixed GGUF, MLX, and document workflows. DeepSeek V4 Flash uses a separate Unsloth Desktop path because of its sharded GGUF packaging. For the curated Bonsai 27B build, try Locally AI and first confirm that its catalog shows the model on this Mac.

Can I upgrade the Mac mini M6 to more unified memory later?

No. Apple-silicon unified memory is integrated into the chip package and must be chosen at purchase. Some Mac mini owners use “upgrade” to mean internal or external storage, but storage capacity does not give an LLM more RAM.

Are these Mac mini M6 local AI speeds measured?

No. Every speed on this page is a formula range based on Apple’s published memory bandwidth, model size, active parameters, and a cooling-aware efficiency range. App, backend, context length, and thermals can change real results.