Anyone clustered multiple 512GB M3 Ultra Mac Studios over Thunderbolt 5 for AI workloads?
Daisy chaining 3 x M4 iMacs together to use all 3 screens and all 3 CPU/GPU | MacRumors Forums
Local host 3 Mac Studios stacked = private AI fleet for the whole office
You can turn a cluster of Macs into an AI supercomputer in macOS 26.2
Will this work with Mac Minis or MacBooks?
Do I need macOS 26.2 on every machine?
Why not just buy the 512GB single Studio and skip the cluster?
Isn't that wonderfull news
You can turn a cluster of Macs into an AI supercomputer in macOS Tahoe 26.2
https://share.google/ABnjZP4kup7n2pMMW
With the new Mac Studio (M3 Ultra, 32-core CPU, 80-core GPU, 512GB RAM) supporting Thunderbolt 5 (80 Gbps), has anyone tried clustering 2–3 of them for AI tasks? Specifically interested in distributed inference with massive models like Kimi K2, Qwen 3 coder, or anything in that scale. Any success stories, benchmarks, or issues you ran into? I'm trying to find a video on YouTube where someone did this and I can't find it. If no one has done it, should I be the first?
A few days ago, I shared our 8x 4090Ds rig setup. It’s a beast, but let’s be real, not every office has the electrical infrastructure, the specialized cooling, or the massive budget to build and maintain a local supercomputer.
So we also looked the other way: horizontal. 3 used Mac Studios on my desk + every junk laptop we could find in the office. Fully local AI fleet, no cloud, no data leaves the building. Here's the build:
3 Studio M2 Ultra, 192GB / 2TB each. 100+ "free-range" office laptops. Qwen on each Studio, a LAN router + ComfyUI for img gen.
Don't see many cross-platform Mac+Win fleet builds so here goes
Hope this shares some real value.
100+ "free-range" office laptops. The kind that lag when a 3rd Chrome tab opens. No dGPU. Battery lasts 40 mins if you're lucky
Qwen 3.6-35B-A3B on each Studio via Ollama. A LAN router + ComfyUI + img gen for the rest
Why this exists:
Our team needed auto-generated social media content, product posts, images, scheduling, research docs... without:
- uploading business docs to some random cloud
- leaking internal convos to whoever's API we're using
- paying per-seat SaaS tax for smth we can run ourselves
We ain't a dev shop. Half the team is happy with Windows Update weekly, the other half on Mac. "Terminal" is a scary word. They just click "generate" and get output.
The old way was tragic, one machine, one LLM, one API key. Growth team runs a SQL query -> model freezes -> everyone else's agents hang. System looks alive, nothing comes out. Then 3 more people retry the same query. Death by single-queue
The queue:
Conventional answer is scale vertical bigger GPU, more VRAM, one mega-machine. Doesn't fix the single queue. One heavy query still freezes everything. And when that machine dies, everyone stares at "connection refused." Going horizontal instead 3 machines, each independent, each with its own queue means nobody blocks nobody. A router sends each request to the least-loaded engine. Linear throughput scaling, fault tolerance, and you expand by adding 1 more machine, not forklift-upgrading the whole rack.
Grid (the router we use) saves us because it doesn't have one queue it has per machine. Each engine queues internally. Heavy query -> machine A. Caption gen -> machine B. Nobody blocks nobody. 3 machines = 3 queues, each clearing at ~80 tok/s on Qwen's MoE. A heavy analysis might take 30s on one machine while the other two serve 20 lightweight requests at the same time.
Bottleneck went from "one queue everyone fights over" to "how to stack 3 Mac Studios without them falling over." Way better problem
The math:
M2 Ultra = 800 GB/s bandwidth. 192GB unified memory. Qwen 3.6-35B-A3B (MoE, 3B active) at 32-64K context per session. Per Studio handles ~17 concurrent sessions. 3 Studios = ~50 concurrent. At 25% concurrency, that's ~200 employees. 500-token response at peak: ~12s. Wait time under half a second. Headroom for days.
24GB VRAM hits OOM at ~2 concurrent 64K sessions. Not a dig, just physics of the hardware.
The cost:
3 Mac Studios: ~$17k total
Power draw all 3 under load: ~300-385W
No data leaves the building
Vs cloud equivalent comparable throughput but your data stays in-building
Scale:
Vertical scaling means buying a bigger machine. But you hit a ceiling, no bigger GPU exists, no more VRAM slots. Every upgrade means migrating everything, reconfiguring, downtime. Horizontal instead? Add another Mac to the stack. The router picks it up. 3 Studios today, 4 tomorrow, 6 next quarter. The ceiling isn't the hardware it's how much desk space you got left.
Things you should keep in mind before stacked Mac Studios like this:
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LAN or nothing. No LAN = no agents. If the internet bill goes unpaid, or your wifi goes down ur entire fleet disappears. Just a room full of people staring at "connection refused"
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Employee takes laptop home at 6PM? They now own an expensive paperweight. Agents live in office LAN. "It's a privacy feature not a bug." Remote Desktop may help if they really need it. Or tell them to touch grass idk
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Not zero-config yet. Each laptop needs an agent gateway configured once (~10 mins). My non-devs can't do that. Looking for a "my auntie can join the fleet" solution if anyone's solved this
Isn't that wonderfull news
You can turn a cluster of Macs into an AI supercomputer in macOS Tahoe 26.2
https://share.google/ABnjZP4kup7n2pMMW