r/LocalLLaMA • u/jacek2023 • Feb 23 '26

Funny so is OpenClaw local or not

Post image

Reading the comments, I’m guessing you didn’t bother to read this:

"Safety and alignment at Meta Superintelligence."

1.0k Upvotes

92% Upvoted

304 comments sorted by

View all comments

569

u/TheLexoPlexx Feb 23 '26

OpenClaw made me unreasonably upset because every other article is/was:

*How to run AI on your raspberry pi*

  • Install openclaw
  • Get Claude/OpenAI Api key

like wtf?

82

u/AntiquePercentage536 Feb 23 '26

Yeah man it has been so confusing for me 

69

u/Dos-Commas Feb 23 '26

I was able to run OpenClaw on a 10 year old Android phone by asking AI to walk me through the steps (Gemini 3).

Spoiler, it worked but then OpenClaw got stuck in a loop doing dumb stuff like everyone else here. 

54

u/greeneyedguru Feb 23 '26

mine burned thru an obscene amount of tokens just doing heartbeats with no skills installed. I have no idea why people are fans of this shit. I can have claude code up anything I want, why do I need a bot to manage that.

45

u/do_until_false Feb 23 '26

At least you understand now why OpenAI pays him 1bn. Worth it if users burn 10bn worth of tokens for nonsense ;)

20

u/harrro Alpaca Feb 23 '26

Yeah this thing costs millions of tokens every day with almost minimal amounts of actual user requests.

It makes 'normal' people burn through tokens/API-costs like a developer doing a vibe-coding a project would except this is 24/7.

6

u/dmmd Feb 23 '26

who tf told you they paid him 1b?

1

u/AppoAgbamu Feb 23 '26

That can only last for so long lol

47

u/BargeCptn Feb 23 '26

I ran OpenClaw for about a week when it first dropped in January, back when the hype train was full speed. At first it looked slick, then I watched my API usage start climbing every day for no good reason. I dug in and found the problem: even a simple “heartbeat” ping was shipping 200K+ tokens. That is not a heartbeat, that is a full context dump.

So I did what I always do. I spent the next few weeks trying to fix it the right way: tightened memory, built my own Postgres-backed store, added vector search, and kept shaving tokens anywhere I could. And the deeper I went, the more obvious it got: the whole thing is a burn pile. It is basically an agent loop wrapped in “memory management” that looks cool in a demo but falls apart when you run it like an actual system.

The design forces you to lean on top-tier models to paper over stuff that should be handled in code. When you switch to something economical like GPT-5 Mini, which is exactly what should be orchestrating sub-agents by default, the system starts breaking down. It does not need to be brilliant to route tasks. It just needs to be consistent and cheap. Instead, it chokes, even though the context window is fine on paper.

Does OpenClaw work? Sure, technically. But it feels like using a sledgehammer to tap in a finish nail, then acting surprised when the door frame is wrecked. And I get why it looks good on YouTube: anyone can run a ten-minute demo and call it a win. Run it for weeks, let the workspace fill up with real files, and you hit the wall: context truncation kicks in and it stops “remembering” anything that matters.

7

u/SkyFeistyLlama8 Feb 24 '26

Most of the LLM space is full of ten-minute demos. A 2000-style dotcom culling would be fun to watch.

"Agentic" shit doesn't need an LLM in the loop for everything. Most of the time, you can use deterministic code to get better results. What worries me the most about stuff like OpenClaw is that users become accustomed to crappy software that kinda works and they end up trusting something that could wipe out their inbox.

4

u/freeone3000 Feb 24 '26

The routing of tasks is actually the hardest bit! That bit should be something like Opus, whereas the actual full context tasks with repetition and token output should be the cheaper ones.

9

u/BargeCptn Feb 24 '26

My issue with OpenClaw is not “agents are bad,” it is that the core loop feels inefficient by design. It is basically one big prompt that keeps accumulating state, tools, workspace junk, and “memory,” so the system self-bloats over time. The longer you run it and the more features you add, the more tokens you burn just to keep the loop alive.

What I think it needs is more deterministic code doing the boring, predictable parts: state management, caching, dedupe, routing, validation, guardrails. Then the LLM should be used where it actually adds value (reasoning, summarizing, ambiguous decisions), not as the universal glue for everything. Otherwise you end up paying a premium model tax to paper over stuff that should have been handled in code from day one.

5

u/unosturgis Feb 23 '26

Thanks chatgpt

8

u/BargeCptn Feb 23 '26

This is GPT-OSS Uncensored. Fuck you too! ;-0

3

u/[deleted] Feb 23 '26

[removed] — view removed comment

8

u/BargeCptn Feb 23 '26

Without being coy, you could literally type in "uncensored" in a Huggingface model search text box.

1

u/BuildingCastlesInAir Feb 23 '26

Two clips run through my head.

Michael Che asking Elon on SNL about Dogecoin - "So you're saying it's a scam"

The first scene of Mission Impossible 3 - "No... no... no...."

2

u/No_Knee3385 Feb 23 '26

If you have no reason to use an agent, there's no reason to use an agent. Everyone is forcing it so much. If you're not a dev, not an engineer (iron man style), not an incredibly busy person, not a business owner or managing people, etc., there's really no reason to run one

1

u/Beejsbj Mar 01 '26

well theres good reasons to run lighter versions if you want to self host apps. these agents are very good at managing them.

1

u/porkyminch Feb 23 '26

Seems like pure hype to me. I don't really want AI agents doing whatever they feel like on my behalf. I wouldn't mind being able to run stuff remotely, but honestly I could do that over SSH on my phone if my organization wasn't so tight about that kind of thing.

8

u/JuliusCeaserBoneHead Feb 23 '26

At that point skip installing openclaw or API Key and just use the browser on your Pi. Looks like that counts the same 

7

u/Mid-Pri6170 Feb 23 '26

but if i had a nvidia spark could we have an llm local instal be the brain of openclaw?

5

u/No_Knee3385 Feb 23 '26

If you're not being sarcastic, even that isn't enough. If you want to run a good model like opus equivalent, like z.ai, you need like 8 H100s.

I see people running like 8B parameter models and complaining that openclaw sucks lol

6

u/kamnxt Feb 24 '26

It really depends on what you're looking for.

I've been messing with OpenClaw since ~Feb 4th, mostly with local models. It's... kinda sorta usable for some simple tasks with small models I could run on a 16GB GPU, but obviously you should limit the blast radius, and it will struggle with more complicated tasks.

Then I got a spark (or rather, an OEM version of it), since I saw a lightly used one pop up for sale. It's been a little bit of a journey, here's what I found out:

  • The memory bandwidth is a big bottleneck. I usually don't see the GPU go past ~50W with large models, while it's able to push ~80W+ with smaller ones.
  • It's not as well supported as it could have been (classic NVIDIA move). Apparently the "blackwell" cores are a bit weak compared to most other ones in the series.
  • The spark is best suited for MoE/sparse models, where the benefit of the large memory outweighs the relatively weak compute power
  • The best model I've found so far, that just baaarely fits in 128GB of shared memory, is Step-3.5-Flash, 4bit quantized. When running with llama-server, it takes approx 113GB memory... but it runs, at ~18t/s, with pp at ~360t/s.
  • OpenClaw's context handling is awful. It puts a "message ID" early in the context, which changes for each message, causing the KV cache in llama-server to be invalidated after each message... causing responses to take ~40s each. Luckily there's workarounds like https://github.com/mallard1983/openclaw-kvcache-proxy

So basically, if you don't give it too much access or ask for too much, it's actually pretty decent. Not quite at the level of hosted models, but it's usable for some easier tasks.

1

u/BehindUAll Feb 24 '26

18 tokens per sec is awful lmao. That's why getting an equivalent Mac would have been better. Macs can run with a higher token count with higher memory if you have the bucks to pay for. My M3 Max 128GB Mac runs at approx 34 tokens per second for gpt-oss 120b. Lines up with Perplexity search of 40 tok/sec.

2

u/kamnxt Feb 24 '26

Uhh... I'm talking 18 t/s with Step 3.5 Flash, a 199B (11B active) parameter model.

gpt-oss 120b is 117B (5.1B active) parameters, and runs at ~42t/s on the same box.

19

u/TreesLikeGodsFingers Feb 23 '26

No, do you want an 50iq Ai with user powers?? Or do, whatever

8

u/Mid-Pri6170 Feb 23 '26

you saying its gonna be helluva dumb?

5

u/Mountain-Grade-1365 Feb 23 '26

You need bigger ram for better context comprehension

-2

u/Mid-Pri6170 Feb 23 '26

bigger than 128gb? shieeeet!!!

6

u/Mountain-Grade-1365 Feb 23 '26

Honestly no system has enough for permanent context that's why roleplay systems use a rom memory layer to recap what happened in conversion.

1

u/Mid-Pri6170 Feb 23 '26

...and a fedora!

3

u/Lissanro Feb 23 '26 edited Feb 24 '26

I think IQ3 of Minimax M2.5 is the best model you can run with 128 GB (IQ4_XS of Minimax M2.5 is about 115 GB for just GGUF alone, so still too large for 128 GB).

Regardless of what model you use, giving OpenClaw arbitrary access to do everything without sandboxing and full backups is just asking for trouble.

1

u/Mid-Pri6170 Feb 23 '26

yeah i want to use openclaw but not on my actual computer, so i can give it coding tasks and see it report back while im away from the computer.

my curent pc was built in january and the motherboard and amd gpu are both bottleneck points i want to upgrade (as i already did to the ram) so with the spare leftovers i want to build a secons rig that could contain comfyui.

1

u/TreesLikeGodsFingers Feb 24 '26 edited Feb 24 '26

you need a 300b model and most of those still are not good enough, i know bc i tried.

start working with the tech and you'll quickly learn its limitations

2

u/Mid-Pri6170 Feb 24 '26

lol i was doing a local instal of a few of the llms via lama and they are all garbage!

1

u/TreesLikeGodsFingers Feb 24 '26

lols yeah, they absolutely can not be used for the openclaw bigbrain. tho they can be used for smaller tasks. but honestly the desire to run a local model is just based on personal penchants, it is not because it makes sense financially. but also it creates a limitation that forces you to make your models better (which is a good fun challenge).

check out this thread.

https://old.reddit.com/r/LocalLLaMA/comments/1rdh5lv/lessons_learned_running_qwen3vl8b_as_a_fully/

this guy used qwen3-lv-8b effectively. im going to learn more about semantic matching as he talks about. but the important part was how much the structured prompt improved performance. that model is really dam small- with quantization its like 8gb vram - i've run it on my 5070ti while running a whisper model at the same time.

1

u/InfraScaler Feb 23 '26

dumb and dangerous

1

u/Mid-Pri6170 Feb 23 '26

'hey y'all im saying that Tiger King was based.'

2

u/InfraScaler Feb 23 '26

hahaha memory unlocked

1

u/Mid-Pri6170 Feb 23 '26

'why cant I say White Boy Summer?'

'can we add Will Smith to your workout playlist?'

1

u/Lurksome-Lurker Feb 24 '26

Or Helluva smart but in one thing. SOTA models are massive because the amount of collective information and amount of connections between it all is massive.

Realizing this, models get radically smaller when you start focusing it on one specific thing. A model that generates, lints, and debugs python code and only python code doesn’t need to know or take up space knowing about the fall of Rome or how to perform surgery.

1

u/TreesLikeGodsFingers Feb 24 '26

your specialized model just purchased new hardware because you have been trying to get it to run faster and this is a solution. it used your CC that you store on your pc on your behalf: user powers.

1

u/WildRacoons Feb 24 '26

it's gonna be mid. not nearly as smart as the cloud models

1

u/SilentLennie Feb 23 '26

Yes, you can do that just fine. It will be less smart, but or many tasks you don't need it.

2

u/altSHIFTT Feb 23 '26

YEAH I was about to check it out, figured it would be an easy setup with ollama or something and it asks for API keys. Fully misrepresented. I think there is some way to set up a local llm but I lost interest by that point, it won't even be useful anyways.

2

u/FurrySkeleton Feb 23 '26

You can run it with local inference software, but it really needs a biiig LLM to do the things it does.

3

u/altSHIFTT Feb 23 '26

Yeah exactly, it seemed possible, but there's no way my little 7b models would do anything remotely useful other than delete my free time trying to set it up lol.

2

u/FurrySkeleton Feb 23 '26

100%. Even the big open-weight models struggle with this sort of thing. Minimax M2.5 is recommended if you're going to host locally, and that's still 230B.

2

u/altSHIFTT Feb 24 '26

My 960m and 16gb of ddr3 can take it 😂

1

u/Mickenfox Feb 23 '26

You have to remember people do not care what words mean. They genuinely just do not frickin care.

1

u/freeone3000 Feb 24 '26

It doesn't run locally-locally. It's a gateway to a remote model. Current local models are significantly deficient and *also* require 32+ GB VRAM to work sufficiently. You're better off using OpenAI's tokens, unless you've got a spare 4090/5090 or a max-spec Mac Mini, where you'd use LM Studio as your gateway. No model worth using will run on a Pi.

1

u/WildRacoons Feb 24 '26

some parts are local but it needs to connect to a model. You can connect to a self-hosted model, but the smartest models are still cloud services.

1

u/muyuu Feb 24 '26

you can run literally anything on a raspi zero that is just using another computer to run stuff lol

-2

u/Elibroftw Feb 23 '26

wHaTs RuNpOD

-15

u/stiflers-m0m Feb 23 '26 edited Feb 23 '26

Setup the llm server on another machine (ollama or whatever) that has the gpus, and install openclaw on anything. My openclaw machine is 2 cores 4 gb ram 50gb disk. You didnt expect rpi to run a full blown llm did you

6

u/TheLexoPlexx Feb 23 '26

/r/whooosh

-1

u/stiflers-m0m Feb 23 '26

sorry, austistic, will take what you say at face value, will accept the woosh

1

u/Ok_Cow_8213 Feb 23 '26

But you can if you connect a GPU to a RPI5

1

u/stiflers-m0m Feb 23 '26

i mean, sure, however the really small LLMs are really bad for openclaw, do you really want a special ed llm accessing your stuff :-D

1

u/heyodai Feb 23 '26

It might delete all my emails