Why give your AI agent one brain when it can have 80+?
Claude. GPT. Grok. DeepSeek. GLM. Seedance.
One API.
The right model for every job.
Pay as you go with Stripe or $OGPU.
Relay.
The future of local AI might not be one giant machine.
It might be clusters.
Jeff Geerling built a 4-node AI cluster using Framework Desktop boards inside an 8U mini rack.
The setup includes:
• 4× Framework Desktop nodes • 5GbE networking • Automated deployment with Ansible • Distributed inference using llama.cpp RPC • Home Assistant power monitoring
Total cost: ~$8,000
What surprised me wasn't the hardware.
It was the conclusion.
Even after building a distributed AI cluster, Jeff's benchmarks show that a Mac Studio M3 Ultra still offers better price/performance for running giant LLMs.
That doesn't make the cluster a failure.
It shows something more interesting.
Clusters make sense when you want to experiment with distributed AI, scale compute across multiple machines, or learn how enterprise AI infrastructure works.
But if your goal is simply running the largest local LLM possible, one machine can still be the better value.
Local AI is evolving in two directions:
• Bigger unified-memory systems. • Smarter distributed clusters.
It'll be interesting to see which approach wins over the next few years.
Allah
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محمد ﷺ
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محمد ﷺ
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محمد ﷺ
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