Cellhasher

Here's an Up to date Breakdown on @Cellhasher with @YourFriendAndy Code: ANDYSFRIENDS at checkout for DIY! Code: ANDY at checkout for Pre-Built Units! Watch it here: youtu.be/EUyRA5CcdMU

@Chain_AlphaX @paoloardoino been a thing on @Cellhasher for a long time now actually!

New day new drop youtu.be/teNGtEWj5B0?si… we got a little @Cellhasher review 👀

x.com/wabdoteth/stat… Sorry @wabdoteth we needed to give this a try.

Something is coming to Acurast. Every block. Every deployment. Every transaction. Fully visible. Soon. 👀

@crusnikpt @Acurast 👀

@Acurast Efficiency is everything. Acurast phone farms pushing the boundaries of distributed networks. I would if @Cellhasher gifted me one of their babys :)

Phone farm check 📱👀 This is what decentralized infrastructure looks like. Not a data center. Not a server rack. A shelf. Some cables. Real phones. Real compute. Show us YOUR setup. #CloudRebellion #MyPhoneFarm 💚

Wait till everyone finds out with @Cellhasher you can deploy your 20phone cluster into an full R&D Lab with various different agents, Research, Security, Audit, Routing, Senior Engineer, Vision, func-call, dev-01 developer dev-02 developer dev-03 developer gateway developer1 guard developer senses developer reviewer meta_engineer research devops data-analyst multilingual writer scout reasoner nanbeige hot-spareguard

Imagine what happens when you use 20 phones all cooking at 10-20 token/s running 24/7 working for you Here is a taste of one Android Phone, a simple deploy of QWEN3.5 running on a 5 year old Android. @Cellhasher

@lukewrightmain Low end compute is amazingly useful even in an ever advancing Tech Sector. Phones have their place!

Here are Android AI @Cellhasher Qwen3.5 + DeepSeek 33B benchmarks. TLDR: its actually worth it if you have old androids for the cheap less than 5w most of these phones operate at. Especially as agents become more deployable and 24/7 hands off or sit and forget. AI model companies will eventually start fine tuning even further to get models into more of a MOE style but tuned directly to the use with Routers, routing each request. Cellhasher is working on this as well. As demand for compute and energy continues, eventually companies will not keep making bigger models and not Company can keep pace with the big ones, they will focus on small local models for retail. We will start with the 5 year old Chipset and Bring you up to speed with some wild results on a newest-chipset. Device: Snapdragon 888 (5 years old chip) CPU only Non-root (28 GB/s memory cap) Rooted devices (56 GB/s) scale ~1.8–1.9x. (using the fastest 4 cores actually outperforms using all 8 cores) Qwen3.5 - 0.8B CPU (4 big cores): 12.54–13.01 tok/s Rooted (1.8–1.9x): 22.6–24.7 tok/s Vulkan GPU (NGL=24): 1.60–1.78 tok/s (7–8x slower) Qwen3.5 - 2B CPU (4 big cores): 9.15–9.36 tok/s Rooted: 16.5–17.8 tok/s Vulkan GPU (NGL=24): 0.78–0.86 tok/s (11–12x slower) Large Models (Non-Root) #p stands for Number of Phones in a parallel pipeline ring made by Cellhasher Swarm AI DeepSeek 33B → 5.89 tok/s (Best was 7.8 tok/s) average is still 5.89 tok/s (12p, d=16, 81% accept) Qwen3.5-35B-A3B → 3.75 tok/s (best was 5.1 tok/s) (3p, d=8, 71.5% accept) Qwen3.5-32B (Coder) → 2.85 tok/s (best 4.8 tok/s) (7p, same-family draft) Rooted Estimate (56 GB/s) DeepSeek 33B → ~10–11 tok/s Qwen3.5-35B → ~6.5–7 tok/s Qwen3.5-32B → ~5–5.5 tok/s Snapdragon 8 Elite Gen 5 plus + 24gb RAM (Android Phone) ~75–85 GB/s memory bandwidth INT4/INT8 NPU usable Well-tuned pipeline Qwen3.5 - 0.8B Model CPU only: 30–45 tok/s CPU + NPU: 70–100+ tok/s Qwen3.5 - 2B Model CPU only: 18–25 tok/s CPU + NPU: 40–60 tok/s DeepSeek 33B CPU only: 15–20 tok/s CPU + NPU (blended): 20–28 tok/s (30 tok/s possible with ideal tuning) Qwen3.5-35B-A3B CPU only: 11–15 tok/s CPU + NPU: 16–22 tok/s Qwen3.5-32B (Coder) CPU only: 10–14 tok/s CPU + NPU: 15–20 tok/s (CPU+NPU is slightly tricky and prefill along with ring pipeline can determine alot, KV cache catching is something i haven't played around with yet) 33B class ~2.5–3.5x over Snapdragon 888 Small models see major NPU uplift Memory bandwidth remains the limiter on large models @Cellhasher has come along way driving inspo from @exolabs over the last few months although things needed to change in order to be correctly managed for android really none of the EXO features are now used, we have our own modification to llama.cpp that overs this ring pipelined parallelism for running LARGE models across however many phones it takes. What's hard is sometimes less phones doesn't always compute to high tokes as some would think less hops will do the trick, in some cases it does other cases like Spec drafting sometimes it doesn't. Regardless Automously running agents 24/7 if i Can run a 80b model at 1-5tok/s on 5 year old Android hardware that runs at 5-15w depending on the amount of phones used, ill take it. If you make the upgrade to the latest generations of phones you get to experience amazing breakthrough of NPU sync and bandwidth optimization that can get you that amazing 20-70 tok/s feel depending per model for every day use. And now im thinking about taking the plunge into 20 of these new phones 20k for 160cores, and 480gb RAM i could possible run the latest and greats at maybe speeds of 10 tok/s.... who knows let me know if you want me to try! (All Phones benchmarked on Ethernet as it offers the best latency over Wifi) (Wifi Still works just slower)

@lukewrightmain @danieldalen @claudeai Our software supports this, A few more updates for 1-2 click deploys will come in this week as-well! Fun times, Helping people who are just getting started.

@danieldalen @claudeai Bro you need help local stuff! What’s your specs Try a MOe model for the tasks you want. Lmk if you need help. Also picoclaw is lighter weight and faster than open claw and can use all the same skills at stuff… been doing this for years actually here’s 80 running

using the @claudeai api but keep getting rate limit errors! help lol.

@MightyBuddha01 they look so cool, it makes it worth it!

@Cellhasher Couldn't agree more. Though Noctuas were overkill.

What it feels like to have phone compute in a market turn like today!

@rukasufall @tengyanAI @openclaw Let us know if you need help. We have 1 click solutions to this :)

@tengyanAI @openclaw Installing OpenClaw via Termux isn’t as simple as it looks. A lot of things in Termux are only emulated, and many conflicts come up. I’ve already managed to launch OpenClaw on my Motorola E22, but it still can’t respond, the API connection drops. For now, I’m stuck at this step.

your old Android phones are a better agent server than a Mac mini. while most users spend $600+ on dedicated hardware for @openclaw, the real efficiency is hiding in your junk drawer. i saw some developers use Termux and Node.js to turn 3 watt devices into constant research hubs. by running npm install -g clawdbot, these discarded screens handle market monitoring and Telegram summaries without a break. 3 phones can roughly match the output of a Mac mini for almost 0 cost. this setup runs Clawdbot 24/7 to pipe private signal alerts directly to a primary device. i suspect the hardware bottleneck for autonomous agents is already dead. compute is now so cheap that our junk phones is sufficient!

Join up twitter.com/i/spaces/1dRKZ…

Cellhasher has a space today with Acurast. We don’t do spaces very often so please come check it out. Should be to long and should have some great convo and topics!

Join Us Tomorrow 1pm EST with @Acurast! Here from speakers @HobbyistMiner, @dspillere , and @Gr8erGoodMining . As we discuss democratizing compute! (link below to set a reminder) x.com/i/spaces/1kvJp…

@d3b0m4n @Acurast Estimating in the next week or two! (Rackmount +20 Phones is still available at the moment though)

@Cellhasher @Acurast When will you be restocking the Cellhasher Classic +20 Phones? Desiring minds would like to know...

Speed running 200 phones onto @Acurast in about 25 minutes. youtu.be/Gzk4TxF9rTY