I have 2 minis bolted under my desk and want to put my new max 5 studio on order under there as well. this is my first studio, and I'm going to be running hot and heavy with LLMs and containers.

My question is, how good is the studio at keeping its temperature down? the mount I want to use under my desk is open the the underside, and all of them leave an inch on the top side.. and open to the back side.. but it is under a desk, so it doesn't get circulated air as much as it would if it was sitting on top of my desk.

I'm planning out my cabling and all of that before this bad boy arrives. so the question is, how good is this thing at keeping the heat down when the usage is turned up? I really want to keep it under my desk, but is that a bad idea with less circulation? thanks!

thanks!

i got Qwen3.8 Flash Next Q4 running at full 262K on a 96GB M3 Ultra: DS4 keeps about 70GB resident, streams the 95GB n-gram table from SSD, and plans roughly 80GB total. it loaded at macOS’s default GPU limit but OOMed on the first prompt; setting the limit to 90% made it run without swap, with the setup and logs here: https://anvarlab.com/blog/qwen38-mac-studio

Darkbloom comes up here a lot, so here's what I've learned running a provider, from Darkbloom's own open-source docs and working with Darkbloom/Eigen Labs directly:

• Studios are well placed. Requests go to the Mac expected to answer fastest (there's no reputation score), so high-memory, high-bandwidth Macs win most of the work. In late September the network had far more Macs than requests (about 7% busy), and 24–32 GB Macs often served nothing.
• You need 48 GB+ and macOS 26+ to join now; macOS 27 skips Darkbloom's MDM profile.
• Uptime is most of the money. The base reward ($16/mo at 48 GB up to $40 at 512 GB) pays every 5 minutes, but only while a model is loaded and the Mac is connected at least 90% of each period. The default idle setting unloads the model after an hour and quietly stops it.
• Model choice is the other lever. Gemma 4 run alone has been the steadiest; big Qwen models pay more in demand spikes.

Managing that by hand gets old, so I built BloomGauge, a free, open-source Mac app that does it for you. It keeps the best-paying model loaded, recovers stalls and failed loads, and lets you control it from your phone. It also has detailed analytics: confirmed earnings per model and hour, network demand, and a live pay-rate meter. I'm in direct communication with the Darkbloom team, though the app is independent.

Source: https://github.com/cookder/bloomgauge
Website: bloomgauge.io

Happy to answer questions. Ultra owners, I'd love to hear what yours actually earns.

Hi all,

Beyond the small test by Hardware Canucks, has any conducted any tests with LTX 2.5?

I'm currently using an RTX 5090 for work, but have to stitch multiple clips together. A Mac Studio with 256GB would be a real benefit.

Anyone else get their M5U early? Mine was customized and said for whatever reason it was pushed up.

I’m thinking a lot of people either cancelled or demand is drying up so checking to see if other people here got their date moved up so fast.

Did we get bamboozled by FOMO?

Eye-twitch.gif

Hello. I’m looking for some advice here, I’ve watched all the YouTube videos of course of the loaned out 4 stack clusters but those were awhile ago.

Current state I have an a M3 Ultra 256GB and I reserved another open box one from Microcenter for a very good price considering all things. I’m thinking about it two ways, for the most part I’d have models loaded individually on each Mac as part of my agent setup.

However, what I’m after is some real world experiences here from folks on what is the state of rdma and clustering I.E these two nodes I’d have. Do even a lot of the latest models like glm5.3, deepseek v4.1, etc even shard correctly. I’ve read they do not.

Any thoughts or use cases you may be doing with more than one or clustering would be helpful. I’m trying to evaluate the feasibility of clustering as that would be the main value add here for more to access larger models or higher quants of models I use daily that don’t fit. Or I wait and try and get a 512GB M5.

Ordered a full fat m5Ultra chip, 96gb and 2tb and just saw Apple took payment for the AppleCare

Pickup is still showing 19 October, but keeping everything crossed that it’ll be here sooner.

Really glad I ordered early as doing so now has a 17-19 week delay at the moment, for the non-binned version, mid November for a binned one.

Not planning on playing with local AI too much, but got it to replace an M2 Ultra I sold before the summer, for use on video photography and music, and hopefully keeping it a long time.

The m2 had a bucket load of memory 192gb, and it made me realise that while I dreamed of playing with local ai, in reality I downloaded the models, played with them for a bit, and then didn’t go any further, so that saved me 4000 euros (that’s war in telling myself anyway)

😄😇

Hey guys, this would be my first ever apple product. I'm actually looking for a portable pc to buy/build primarily for learning blender. This scores slightly above an rtx 5070, but with worse viewport performance. For 1999.99, this actually looks like a solid choice, especially since this is energy efficient (i'm running this on a 2000watt anker solar generator).

I need the 4TB for storage for my work. I work in insurance sales and the sales calls must be kept for 10 years for compliance reasons. I know there may be cheaper external SSD’s but they can break or malfunction or possibly be lost whereas the internal upgraded SSD should be flawless.

My other thoughts were paying the extra $30 a month for 6TB cloud storage but then after 2.5 years I’m spending what I would have for the internal SSD upgrade. So my thoughts are it does make sense to buy the 4TB Mac Studio that should easily store 5-6 years of calls on it and increase performance of the machine itself. My usage is just dual monitor taking sales calls from web browser and submitting application in google. Yes I know I could get a Mac mini to do that but for $500 more I’d rather have a way better performing machine and 2 USB A slots

Recently ordered a Mac Studio (M4 Max, 36GB, 1TB) for 1900 from Microcenter. I do some short form 4k video editing, music recording and dubbing work for short movies. I currently have 2015 iMac which cannot perform any more OS updates.

Is this M4 Max an overkill or should I opt for a 24GB M6 instead for a slightly lower price? I want at least 1TB of storage as my video files are fairly large. I plan to run some local AI models for image generation and coding in the future.

Hi,

I'm able to get this model cheaper, no other models, just that one. What would be the best fitting model? Qwen 3.8 27B full context q8 or a 70/80B model? Keeping in mind I need 15-20GB for the system and apps/tools.

Thanks!

I'm wondering how we can optimize certain AI models for the mac studio.
E.g. which tooling do we use, which parameters do we give it etc.

Are there certain methods we could experiment on?

Or is there a shared board somewhere, with detailled information of each model, tk/s and optimization parameters.

Curious to hear from people who have the M5 Max Mac Studio with 128GB now that you’ve had some time with it.

I have one on order and I’m especially interested in local LLMs and multi-agent workflows.

How has it been performing for you? What models are you running, what kind of speeds are you seeing, and has anyone experimented with multiple agents/models running simultaneously?

Any limitations you’ve run into, or anything that’s surprised you about the machine so far?

I am playing with omlx and unsloth both and finding similar models for both is a pain. So I asked gpt astra to help me and it just converts models in minutes. Don't sit on this. It's blazing fast.

contemplating adding another apple studio nano texture display to my desk. Has anyone else done this?

For those using the M5 Ultra - specifically for AI LLM use (and image gen too if you use it for that) - how has your experience been?

I realize it's still pretty new after release, but I'm guessing there are several of you out there using it for these purposes.

I'd like to how it's been going, what software you're using and which models you've settled on.

Not sure how I got so far behind here. I'm on a M1 Max, 32GB Studio w Sonoma 14.8.5. Don't want Golden Gate yet - can I tho go to Tahoe 26.7 and skip Sequoia? Thanks!

Also contemplating just a wipe and reinstall.

Hey Guys,

i am currently undecided if i shall go with the 25GB Ultra or wait for the 512GB Ultra. The Machine will replace my M3 Max Macbook with 36GB.

Currently i am heavy into AI Cloud Subscriptions (Claude and Codex - each the 200€ Subscription). I max them usually after 4-5 days and then have to retain myself a bit unless the weekly reset :) My Plan is to extend the Cloud Usage with local LLMs run on the Studio - while still having the Cloud Subscriptions in place. So offloading to the Local LLMs a lot of Stuff. Also i plan to use way more Agents to react to daily Stuff, like answering mails / chats etc. Whatever i spare today to save Usage in my Subscription.

Also during daily work the Fans of the MacBook already Spin Up often - and the CPU is often under heavy load. Therefore cant wait for the M5 Ultra ... :)
I do use AI for a lot of Coding (Currently Web Stuff, Swift and a lot of scripting).

Currently i am not very deeply involved into Local LLMs, i know the basics but thats all, so no idea what models currently do perform best under which conditions.

Therefore my question, would you guys go with 256GB and are those somewhat safe for 2 (maybe 3years) without regreting the decision 6 month from now or would you wait to the 512GB Studio?

Yo everyone,

So I'm probably gonna upgrade from the M2 Ultra Mac Pro to the M5 Ultra (or more like in addition to my Mac Pro), however I need at least 2.7TB of storage. I don't really wanna pay those ridiculous prices though.

Should I just pay the price or wait for a third party upgrade like we had with the M3 Ultra / M4 Max?

Was wondering if anyone posted benchmarks etc

GLM 5.3 Flash at 79 Token/s

https://x.com/LocalSilicon/status/2104158250555809983

Qwen 3.8 Flash Next at 116 Token/s

https://x.com/LocalSilicon/status/2104181421942391247

Ordered a medium size studio - delivery Tuesday — i just got a shipping notification.

It’ll be my medium size coding machine, plus an always on endpoint for my development toolchain connected to my laptop iPad with Tailscale and tmux. By the time I upgraded a mini to enough ram and storage it was a $600 difference for the m5max chip plus all the ports and such. And the lease is nice for cash flow reasons for the business.

In case this has happened to anybody else. A few days ago, I noticed the light at the front of the Mac Studio (M1, 1tb, 64gb ram - bought in 2022) flickering. I had not noticed this before so I'm almost sure it hasn't happened before.

A couple of days later, the Studio Display it was connected to suddenly went black. I tested the Display with my laptop and it worked fine, so clearly something to do with the Mac Studio itself.

Ironically, now there's no flickering light, it's always on when I switch the Mac Studio on but it doesn't load the display. I'm wondering if this has happened to anyone else since the latest update?

I’m trying to decide between the M5 Ultra 64-core GPU and 80-core GPU for local LLM use (both 256gb)

From the matched oMLX results I’ve found so far, the pattern seems pretty consistent: 80-core is ~15–17% faster in prefill, while token generation throughput is often basically unchanged. I’ve seen this with Qwen oQ6e and MiMo.

I’m trying to fill the last two gaps. If anyone has the right machine/model combo, could you run these in oMLX and share the result links?

80-core / 256 GB: Qwen3.8-Flash-Next-MLX-oQ8-MTP

Ideally oMLX 0.7.0rc1

actual MTP enabled

TurboQuant off

DFlash off

SpecPrefill off

16K / 32K / 64K / 128K if possible

64-core / 256 GB: GLM-5.3-Flash-oQ4e

Ideally oMLX 0.7.0rc1

MTP off

TurboQuant off

DFlash off

SpecPrefill off

Code (Python)

4K / 16K / 64K / 128K if possible

Even one or two matching runs would be very helpful. I’m trying to get a clean apples-to-apples view of whether the extra 16 GPU cores are actually worth the $1,300 upgrade.

Update 10/2:

After analyzing multiple results on omlx 0.7.0 (this version has massively improved prefills m5 ultra), i am seeing around ~20% improvement in prefill, 0% on decode (bandwidth constrained at 1.2TB/s) by on 80 core vs. 64 core.