OpenClaw is a personal AI assistant that runs on your laptop, talks to local or remote models, and exposes itself through every messaging app you already use.
It can actually does the work and gets things done.
OpenClaw is written in TypeScript.
It is open source and available for everyone to download on GitHub.
At the time of writing it had 383k stars on GitHub.
It has the largest community, largest skill marketplace, most comprehensive “it just works” tool catalog. Default skills cover code, web, files, calendar, mail, and lots of integrations.
OpenClaw is general and more reactive AI agent.
There are lots of skills available, low setup overhead, no native learning system.
Who should use it
That said, if you plan to do anything meaningful with OpenClaw bare in mind that power consumption and hardware requirements are very high and as such it remains prohibitive for everyday users. This is painfully true for the local model size of 70B+.
Just price of the one old 2022 NVIDIA GPU RTX 4090 starts from $1,600 (at the time of writing).
OpenClaw is not for everyone. People running it will need a decent, up-to-date rig, cover increased climate control expenses, and face extremely high electricity costs.
All of this comes with a high price tag and this is a major barrier for everyday use.
It remains best suited to tech experts.
Caveats
~500k lines across hundreds of files, in a layered architecture nobody fully understands.
Isolation is enforced at the application level inside a single shared process – if one skill misconducts, it can in theory reach anything OpenClaw can reach, which is most of your machine.
What’s required to get it running
You will need a decent hardware to run it.
Forget about gaming rigs as top of the line.
There are no compromise with AI machines, you will need as much RAM as you can get, NVMe SSD storage is non-negotiable, best GPU’s, tons of electric power, water cooling – you’ll need the best and latest in every category.
OpenClaw is extremely resource and power hungry
Here are hardware requirements for heavier use with 30B class (better known as the agent “sweet spot”)
CPU: 4+ vCPU
RAM / unified memory ~32GB
GPU VRAM (for the discrete GPU) ~24GB (only at lower quants)
Storage: 80 GB SSD+
Energy demand is extremely high
Good god! Plan for higher electricity bills.
Only GPU’s during average run generate 900 W .
This is just for the 2 old graphic cards RTX 4090 from 2022.
You will also need to use water cooling for the machine and work out the additional climate control spending for the room where this machine will be located.
2× RTX 4090: ~900 W average during the run – this is called active inference (generating tokens). For idling only they will suck 200 W.
Again, this is just for the 2 old graphic cards from 2022.
As we can see line “personal AI assistant that runs on your laptop” is not entirely true.
The one who runs OpenClaw will have to get a respectable desktop rig to use it for any meaningful work – otherwise it will be just a slow and boiling hot science experiment.
What about Security
OpenClaw is not safe to run directly on your main machine – period.
The shared-process, application-level permission model means a misbehaving skill – including one pushed by prompt injection – can reach files and tokens it shouldn’t.
Run it inside a VM is a must for evading this entire class of problems.
Final thoughts
The trend is clear: AI hardware is becoming more specialized, power-hungry, and expensive, but also more efficient per unit of compute.
Anyone running OpenClaw must invest not just in GPUs, but in entire ecosystems of power, cooling, networking, and software optimization to unlock its full potential.
Darn – it looks like you’ll need an engineer to run it.
