Dappnode

Run Private AI agents 24/7 to increase your daily productivity.
Earn rewards running your web3 node at home.
Zero hassle, it just works

[Dappnode @dappnode]

Don't have a nexus account yet?
https://t.co/PhLqIZiNO9

[Dappnode @dappnode]

Qwen 3.8 27B is the model that packs the highest intelligence per size

It's fast, smart, and very good with agentic tasks

It can handle pretty much everything you throw at him

And it's also Free🤑 for a limited time in Nexus right now

⚡️Go squeeze every prompt from it! 🥵

[Dappnode @dappnode]

@raopreetam_ @d_gusakov @Heracles1337 @ethereum a few minutes installing dappnode and you get a bunch of neat stuff packaged with it! UI, Tailscale/Wireguard for remote access, a UI for validator keys and a bunch of neat packages in the Dappstore!

[Dappnode @dappnode]

Easy! Give OpenClaw or Hermes (both available in Dappnode) your problem and ask them to query you on what your preferences are, what would you like, etc.

If you use Nexus as the model provider, you keep your personal info private from any profiling company 🕵️

If some of the class info is in PDF, feed it to it, if it's behind password... again, feel free to give it your account details because... the filesystem is yours and only yours and the model provider can't read your password!

[Dappnode @dappnode]

If you are not running your own agent you are behind

"But it's too complicated"

In 1:47 seconds you can have it running on your Dappnode

Get your agent, fully private & self-sovereign

Comment 👇which thing you'd die to automate in your life and we'll make a video of how

[Dappnode @dappnode]

@CryptoChrisG Upper class for you, ser.

Jk aside, wdym class selection?

[Sebastian Bürgel @SCBuergel]

I almost missed the IMHO most catastrophic @ledger vulnerability:
h/t @Fatalmeh who brought it onto my feed

[gusakov.eth | Lido @d_gusakov]

Every EVM developer should have a local archive @ethereum node and never trust RPC providers or spend money on RPC subscriptions.

I run archive Reth + Prysm on my @dappnode, and it works like a charm. 4TB SSD is more than enough

[Dappnode @dappnode]

Every home validator is one more vote for a resilient, censorship-resistant Ethereum. Thank you for funding that.

[Dappnode @dappnode]

Thank you❤️

TheDAO Fund's Ethereum Security round on Giveth sent Dappnode 5.6343 ETH: 1.2227 from the community, 4.4116 matched.

Here's how that money becomes Ethereum security: easier home staking → more solo validators → a more decentralized, safer Ethereum.

[Dappnode @dappnode]

Indirectly, we dropped Smooth's fee from 7% to 5%, so solo stakers keep more of their rewards. Solo staking must stay viable (and that includes rewarding them over centralized players)

[0xtim.eth (90 seconds to crypto) @haochizzle]

kinda crazy my @dappnode video from 2023 is still one of my top performers on youtube

https://t.co/8kv4h8LP5h

[Dappnode @dappnode]

@haochizzle Maybe you should do one on how to run Agents on Dappnode now!

[Pol Lanski 🥩,🤖 @Pol_Lanski]

The guys from @exolabs , which we have used extensively in @dappnode, dropped https://t.co/KWu4ep6MXM.

For virality, they let you claim your name already.

https://t.co/hx4uiEwi6J

[Dappnode @dappnode]

Testing on Dappnodes

[Syzygy Research @syzygyeng]

Today, we're introducing Mach-1 Additive, a 35 billion parameter model that can inference without ever multiplying by a weight. At 1.7 bits per weight, Mach-1 recovers 95% of the performance of the original full precision model, Qwen 3.6 35b, across 12 agentic and reasoning benchmarks, while being 10x smaller.

At 7GB, Mach-1 comfortably fits on consumer laptops with speeds of up to 120 tokens per second, making local inference not just feasible but useful.

Unlike algorithms like BitNet, our approach requires minimal retraining, under 15 GPU hours, making it scalable to massive LLMs. Over the coming weeks, we will be announcing and serving models of up to 3 trillion parameters compressed using our algorithm. For now, you can visit our website to play with Mach-1 directly in your browser, or download our desktop app.

We couldn't be more excited to launch Mach-1. We're looking forward to an energy efficient future for AI, powered by scaled intelligence density.