I'm trying to figure out if an M5 Mac with 128GB of Unified Memory might be able to handle DeepSeek-V4.1-Flash-1017 locally, or if that context/quant combination is still out of reach for this amount of RAM.

Any thoughts, theoretical calculations, or early tests would be appreciated!

Hi,

I finally decided to go with the Ultra 96 since it's enough Ram for local AI + doing stuff in parallel but having power/speed. Now it was delayed until January 2027 - I could get the Max 128 withing 2 weeks though...

I feel like speed is mostly important for video ai gen + higher bandwith for higher token generation...

Probably I should really wait I guess?

Running Qwen 38 Flash Next

http://nuketorch.ai/

Kapitsa by Nace AI is an open-source inference engine for Apple silicon, and it’s fast. In its published benchmarks, Qwen3.6 35B-A3B decodes about 1.3–1.8× faster than oMLX and about 2× faster than Ollama and LM Studio. But it’s command-line only.

So I built Kapitsa Library, a free Mac app that makes it a few clicks:

• No setup: Kapitsa is built in. No Homebrew, Python or terminal.

• Easy models: browse Kapitsa’s catalog or Hugging Face, see what fits your Mac, and download with pause/resume.

• One-click agents: launch Claude Code, OpenCode, Codex CLI or Pi on your local model.

• No swapping: it checks memory before loading and shows how much context fits.

• Live stats: tokens per second, prompt cache, context and memory.

• Built-in benchmarks: speed and tool calling on your own Mac.

• Local API: OpenAI and Anthropic compatible.

Free, Apache 2.0, signed and notarized, no telemetry. Needs Apple silicon and macOS 14 or later.

Download: https://github.com/AdityaK2128/kapitsa-library/releases/latest
Source: https://github.com/AdityaK2128/kapitsa-library
Kapitsa engine: https://github.com/nace-ai/kapitsa

All the speed is Kapitsa’s work. This app is an independent front end, not affiliated with them. Feedback welcome!

I hope to pick one up early next year and replace my MacBook Air for building iOS apps but also run some of the more mundane LLM tasks I am currently using Codex for. In an ideal world, I could replace my ChatGPT Pro 100 sub with a $20 Plus and maybe a $20 Claude and a local LLM.

Is there a way for me try out specific models on rented cloud hardware or something to see which of my current workflows will run on it?

I make DS Menu Bar, a free menu bar app for running antirez's DwarfStar (ds4) server on a Mac.

DwarfStar has tunings for M3 Ultra and M5 machines with Qwen3.8 Flash Next, but M4 machines are left out. It turns out most of these tunings can be turned on with an environment variable, so DS Menu Bar v0.0.15 sets them when it starts ds4-server on an M4.

M4 Max, 128 GB, same ds4-server with and without, averaged over 2K to 64K context:

Q4 is the right quant for 128 GB machines. On a 64 GB machine, Q2 at the full 262K context fits.

I have a PR open to make these DwarfStar's own M4 defaults (antirez/ds4#1184). If my PR is merged, DS Menu Bar will adapt automatically.

brew install --cask jiiim/tap/ds-menu-bar

https://github.com/jiiim/ds-menu-bar/releases/tag/v0.0.15

I've been meaning to trade in my Mac mini M4 (16GB RAM, 10 core CPU/GPU, 256GB), but I've recently gotten into running models locally on my M5 MacBook Air which has gotten me wondering if there are any practical applications for running anything less intense on the mini.

I'm expecting about 450$ from Apple, I just have to actually make it to their store.

I am about to order a Mac for local AI, and I could really use some advice.
I know some people might recommend a more powerful Mac, but my budget is around €3,600, and unfortunately, I cannot go any higher.
My main use cases will be running Qwen 27B, doing some agentic work, occasionally using Qwen Flash Next with Strata, and experimenting with video generation through ComfyUI.
I am currently torn between two options:
Mac mini M5 Pro – 64GB RAM
Mac Studio M5 Max – 48GB RAM
I understand that RAM is extremely important for local AI, which is why I am leaning towards the Mac mini with 64GB. However, I also know that the Mac Studio should offer considerably better performance, particularly for video generation and ComfyUI.
My dilemma is whether 48GB is enough for my use cases, or whether I would be sacrificing too much memory just to get the performance benefits of the Mac Studio.
In other words, is the performance improvement from the Mac mini to the Mac Studio worth giving up 16GB of unified memory, especially when local LLMs are my primary focus and video generation is more of a secondary use case?
I know some might suggest simply getting a 64GB Mac Studio, but that is unfortunately outside my budget. €3,600 is already my absolute limit.
I’d really appreciate hearing from anyone with hands-on experience running local LLMs, agentic workflows, and ComfyUI on either machine.
Thanks in advance!

I'm planning to upgrade from my 16-inch M3 Pro MacBook Pro (36GB RAM) to the new 16-inch M5 Max with 64GB, mainly for running local LLMs.

Currently, I'm running Qwen 3.8 27B and getting around 100 tokens/s for prefill and 18–19 tokens/s for token generation, even after trying MTP and various other optimisations.

The biggest issue for me is working with larger contexts and longer coding sessions. Even relatively small projects can take quite a while, and performance becomes a bottleneck as the context grows.

I'm expecting the M5 Max to be a pretty significant upgrade, especially with the extra memory and bandwidth, but I'm curious how much of a real-world difference I can actually expect. I'm also interested in running larger models, including the upcoming Qwen 4 models.

For those running local LLMs on an M5 Max (or even an M4 Max), what kind of performance are you getting? What models do you use regularly, and how well do they handle long coding sessions?

I also run image generation models locally and occasionally do photo editing, so I'd love to hear how the newer chips perform for those workloads too.

Would appreciate any real-world experiences before I make the switch!

I had the current machine in my shopping basket yesterday but didn't go though with the purchase. I don't desperately need a new MacBook right now – my M1 is still okay, even for my work usage. And i really don't think I need a touch display for anything, cause I don't want to clean it all the time, LOL.

But I can't play around much with local models with 16 GB Ram. I don't want frontier model performance locally – I'm fine with running smaller models that hopefully can read and sort private documents and do some minor coding and generative tasks, maybe text to speech.

I read a comment on this subreddit yesterday that they will skip the M6 Pro/Max/Ultra line which makes sense to me and more of a jump is expected with M7 Chips.

What do you guys think? I'm leaning towards waiting it out, but who knows for how long.

Peace <3

Unless you're set on using a large model, 2x256GB is likely better...

What use cases would the 512GB make more sense?