Distributed inference for the people. Private and public mesh, sharing hardware for inference. https://xitter.twitterapi.xyz/t.co/yqbhmITeYQ
github.com/mesh-llm/mesh-llm
Joined October 2026
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Mesh LLM retweeted
Full writeup on shared compute coming soon. Until then, here’s another look at what plugins can do.
Left (Machine 1): Agent Palmer has no LLM attached. It runs entirely on shared compute from the relay.
Right (Machine 2): A regular MacBook running a local @QwenDevs model, sharing its compute with anyone on the network who needs it.
The little black square: Machine 2’s floating window. It shows live activity even when you’re outside the shared compute view.
Bonus: I added USB support to an ESP32 unit that stays synced with Machine 2.
@Mesh_LLM handles all of it behind the scenes.
IMO shared compute is still extremely underutilized.
Think of it as blue-collar AI: it runs quietly on your relay and handles background tasks and batch jobs, powered entirely by your community’s machines.
And since @buzzdotxyz is open source, you can run all of this on your own servers. That’s one small step for buzz, but one giant step toward sovereignty for all mankind.
New Mesh plugins for Apple Silicon:
⚡ Uzu: high-throughput Metal inference for Qwen 3.8 & more
🧠 DwarfStar: run huge DeepSeek V4 models locally
💾 Slotstream: SSD-backed MoE for Macs with less RAM
github.com/Mesh-LLM/uzu-runt…
github.com/Mesh-LLM/ds4-plug…
github.com/Mesh-LLM/slotstre…
Mesh LLM retweeted
this was fun to build
- fork of signal
- agent built with GDK
- using open weights model
- served via e2ee mesh-llm
- via private GPU TEE
- making private search tool calls
- paid for with ₿ over LN
a cool stack of permissionless & open source tech all working together!
An agent inside Signal using decentralized compute paid for with bitcoin
@moneyball demos a fork of Signal built by @matbalez using @Mesh_LLM and @lexeapp ↓
Timestamps:
0:00 - Demo: agent inside Signal
10:51 - The economics of decentralized compute
14:39 - Running inference at home
Mesh LLM retweeted
Right on - this is what we made MeshLLM for (well that and some procrastination: github.com/mesh-llm/mesh-llm
Metal, CPU, CUDA (various), ROCm, Vulkan, x86_64, arm, windows/mac/linux and appropriate combinations.
(fingers are sore).
we have shifted a fair bit of dev to buzz to try out multi player agents, just to see how it goes. Some findings from the other month: engineering.block.xyz/blog/s…
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Right on - this is what we made MeshLLM for (well that and some procrastination: github.com/mesh-llm/mesh-llm
Metal, CPU, CUDA (various), ROCm, Vulkan, x86_64, arm, windows/mac/linux and appropriate combinations.
(fingers are sore).