Replying to @DingusUSA
@Cellhasher great way running old phones without batteries or even without screen and provide compute power to eg @Acurast
Over 300,000 phones are now onboarded to Acurast.
Another major milestone.
These hundreds of thousands of phones are helping build the biggest decentralized compute network in the world, using already existing hardware. No data centres needed.
The next cloud is in your pocket.
Cellhasher retweeted
And here I am, running 0.02% of the network out of my home thanks to @Cellhasher and some wicked automations.
Cellhasher retweeted
What's everybody doing this Monday morning I'm just preparing some phones for @Cellhasher to on board some more devices for @Acurast
Check out my channel for videos on this project and many others
youtube.com/@trailerminer965…
Cellhasher retweeted
Who else is mining @Acurast with their spare cellphones or @Cellhasher device? Nice little pump lately!
Tune in as we discover the latest DePIN x AI trends with @HobbyistMiner, @YourFriendAndy and @Cellhasher!
xitter.cf/i/spaces/1RKZzzEjZpzKB
What happens when decentralized compute and physical hardware meet autonomous AI?
Join @acurast, @hobbyistminer, @YourFriendAndy, and @Cellhasher as we explore the future of DePIN x AI Agents and what comes next for the stack.
Don't miss it. Tomorrow, July 29th at 2:30 UTC.
Set a reminder: xitter.cf/i/spaces/1RKZzzEjZpzKB…
Cellhasher retweeted
Replying to @Acurast
@Acurast feat @Cellhasher
Managing 31 Androids' from various manufacturers is a lot easier this way.
Next step is moving automations/recovery to a ubuntu instance, while preserving Cellhasher as the cockpit.
Put your (old) phones to use, folks! 👇
Cellhasher retweeted
Tonight’s Project!
Onboarding my remaining 16 Phones onto @Acurast with my @Cellhasher for AI Compute
Learn More About Acurast
youtu.be/HiXb0n3UUys
Cellhasher retweeted
🎁Congrats to KayTrim for winning the @Cellhasher Kit Giveaway!
Please email me at [email protected]
This Giveaway was part of the video "Use your PHONE for Ai and Get Paid in Crypto!" youtu.be/HiXb0n3UUys?si=zEjS…
@Acurast
Cellhasher retweeted
Replying to @Chain_AlphaX @paoloardoino
been a thing on @Cellhasher for a long time now actually!
Cellhasher retweeted
New day new drop youtu.be/teNGtEWj5B0?si=v0EC… we got a little @Cellhasher review 👀
Cellhasher retweeted
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
Cellhasher retweeted
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)
🚀 Introducing the Qwen 3.5 Small Model Series
Qwen3.5-0.8B · Qwen3.5-2B · Qwen3.5-4B · Qwen3.5-9B
✨ More intelligence, less compute.
These small models are built on the same Qwen3.5 foundation — native multimodal, improved architecture, scaled RL:
• 0.8B / 2B → tiny, fast, great for edge device
• 4B → a surprisingly strong multimodal base for lightweight agents
• 9B → compact, but already closing the gap with much larger models
And yes — we’re also releasing the Base models as well.
We hope this better supports research, experimentation, and real-world industrial innovation.
Hugging Face: huggingface.co/collections/Q…
ModelScope: modelscope.cn/collections/Qw…
Cellhasher retweeted
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)
xitter.cf/i/spaces/1kvJpMvVoPdxE
Cellhasher retweeted
Thank you @Cellhasher !
Just received my unit from a recent giveaway. Very much appreciated 🙏
Cellhasher retweeted
Shoutout to @Cellhasher for hooking me up with another Cellhasher.
Top unit is the original Cellhasher I reviewed 2 years ago, bottom one is the latest revision.
We’re going to solo mine with this one. What coin do you think we will pick?































