Can a 16GB Mac run a local LLM?

Yes. A 16GB Apple silicon Mac can run smaller 3B to 8B-class models comfortably at Q4_K, and some 12B-class models in tighter configurations. Context length, other open apps, and backend choice still matter.

What is the best quantization for running local LLMs on Mac?

For most people, Q4_K is the best default because it keeps RAM use manageable while preserving useful quality. Q6_K is a quality-first step up if your Mac has more headroom, and Q8 is usually only practical on higher-memory Pro, Max, or Ultra Macs.

Is MLX faster than Ollama on Mac?

Often yes, especially on Apple silicon with popular MLX-converted models, but not always. Real-world speed depends on the model, quant, context length, and whether the backend is tuned well. This calculator uses conservative tok/sec ranges instead of claiming a universal winner.

How much RAM do I need for a 32B or 70B local model on Mac?

A 32B model is usually most practical on 48GB to 64GB Macs at Q4_K or Q5_K. A 70B model is generally a 96GB to 128GB-class machine conversation, with Q4_K being the most realistic local tier.

Free Tool · macOS · Local AI

Mac model fit calculator

Compare real Apple silicon Macs against real open-weight model sizes. Use the calculator for recommendations, or jump into Will It Fit? to see the full cross-model table with Q4, Q6, Q8 memory estimates and realistic fit status.

42 verified Mac entries 88 model profiles Q8 · Q6_K · Q5_K · Q4_K · Q3_K · Q2_K M3 Pro · M3 Max · M4 Max tok/sec anchors

1. Pick the job

What are you trying to do?

Mac configuration

What this recommendation optimizes for

Prioritize coding strength, decent speed, and realistic daily local use.

Selected Mac

Chip: M3 Pro
GPU: 14 or 18-core
Neural Engine: 16-core
Bandwidth: 150 GB/s
Thermals: Active

2. Recommended setup YES

DeepSeek R1 Distill Qwen 32B

One of the more practical R1-style local options.

Suggested quant Q5_K

Q4 memory 19GB

Est. speed 5–7 tok/sec

Loaded RAM 23GB

Headroom left 13GB

Best use Reasoning-heavy assistant

Why this model

Reasoning-heavy assistant
Planning

What to know

One of the more practical R1-style local options.

Conservative Apple-silicon range anchored to community MLX / Ollama / llama.cpp reports.

3. Shortlist

Best matches for this Mac

Model	Type	Quant	RAM	Headroom	Fit
DeepSeek R1 Distill Qwen 32B Reasoning-heavy assistant	chat	Q5_K	23GB	13GB	YES
Qwen 2.5-Coder 7B Best small coding pick	coding	Q6_K	7.7GB	28.3GB	YES
Qwen 2.5-Coder 32B Large repo work	coding	Q5_K	23GB	13GB	YES
DeepSeek Coder 33B Big local code reasoning	coding	Q5_K	23.6GB	12.4GB	YES
Code Llama Instruct 13B Higher-quality conversational coding	coding	Q5_K	10.5GB	25.5GB	YES
Qwen 2.5-Coder 14B Smarter coding	coding	Q5_K	11.2GB	24.8GB	YES
Phi-4-coder 14B Reasoning-aware coding	coding	Q5_K	11.2GB	24.8GB	YES
StarCoder 15B Smarter code generation	coding	Q5_K	11.8GB	24.2GB	YES

Mac configuration Use case Minimum quality tier Max RAM at selected tier Sort by

Selected Mac 14-inch Pro M3 Pro · 36GB

Q4 fits -

Q6 fits -

Q8 fits -

Full comparison

Will it fit?

Showing models that match your filters.

Model	Type	Q4_K	Q6_K	Q8	Fit	Headroom	tok/sec	Use case

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Mac database

Corrected through March 27, 2026

Added: M2 / M3 / M4 Air and Pro variants the first pass missed.
Corrected: 2025 Mac Studio is M4 Max or M3 Ultra, not M3 Max.
Corrected: no Apple silicon Mac Pro refresh beyond M2 Ultra by March 27, 2026.
Corrected: iMac is current on M4, not just M3.

How to read fit

Simple fit rules

YES: at least 6GB headroom after the selected quant loads.
TIGHT: it fits, but context length and background apps will matter.
NO: practical loaded RAM exceeds unified memory.
Q4_K: best default. Q6_K: quality-first. Q8: luxury tier.

Quantization guide

What each quality tier really means

Q8

Near-full quality

Best quality, largest memory footprint.

Q6_K

Very strong

Great quality if you have the RAM.

Q5_K

Balanced

Strong compromise between memory and quality.

Q4_K

Most practical

The default sweet spot for most local Mac use.

Q3_K

Fit-first

Use when you need a bigger model to fit at all.

Q2_K

Last resort

Only for experiments or very tight RAM budgets.

Method notes

Sources and assumptions

Mac hardware data verified against Apple newsroom announcements, Apple Support tech spec pages, and Apple compare pages current through March 27, 2026.

The original request included a few incorrect Macs. Corrected lineup notes: no M3 Max Mac Studio in 2023; 2025 Mac Studio is M4 Max or M3 Ultra; no Apple silicon Mac Pro refresh beyond M2 Ultra by March 27, 2026; iMac updated to M4 in 2024.

LLM memory numbers are practical loaded-RAM estimates for GGUF / llama.cpp / MLX-class quantized local inference on Apple silicon. Exact usage varies with context length, backend, batching, and vision adapters.

tok/sec values are conservative Apple-silicon ranges tuned to land near common community-reported results for M3 Pro 36GB, M3 Max 64GB, and M4 Max 128GB rather than theoretical peak throughput.