r/clawdbot

So I'm using Gemma4:26b on my mac studio. It runs. It can see images with uploading it into the ollama interface. Openclaw runs on a vps on a proxmox box right next to it (all in the same local network). I have my heartbeats and my design agent currently configured to the Gemma model. Everything seems to work.

I can't, for the life of me figure out why the agent cannot use the ollama Gemma4 model vision capabilities. It keeps getting aborted via ollama through telegram. What is going on? Has anyone gotten vision capabilities to work via ollama? I really don't want to burn tokens on openrouter or codex for this.

I've configured models.json and openclaw.json for the provider description to include both "text", "image" doesn't seem to help.

Email:

“

Hi,

Starting April 4 at 12pm PT / 8pm BST, you’ll no longer be able to use your Claude subscription limits for third-party harnesses including OpenClaw. You can still use them with your Claude account, but they will require extra usage, a pay-as-you-go option billed separately from your subscription.

Your subscription still covers all Claude products, including Claude Code and Claude Cowork. To keep using third-party harnesses with your Claude login, turn on extra usage for your account. This will be enforced April 4 starting with OpenClaw, but this policy applies to all third-party harnesses and will be rolled out to more shortly (read more).

“

Any different?

Hey r/clawbot! 👋

We’ve just released QCAI for iOS and Android, and we want to highlight its OpenClaw Control Center integration! You can now manage your gateway directly from your phone.

Key OpenClaw Features:

• 📊 Dashboard: Real-time server monitoring and web console.
• 💻 Portal: Direct access to your Node.js ecosystem. This will allow you to access your selected information on the OpenClaw via command shell or HTML (e.g., you can view the OpenClaw generated output directly or remotely control your Antigravity/Claude Code/WeChat and many other apps in real time
• 💬 Gateway Chat: Direct LLM link for context-aware gateway interaction.
• 🧠 Context OS: Submit your approved mobile device sensor data to your OpenClaw gateway (e.g., calendar, walked steps, etc) and let OpenClaw do a real time plan/recommendation via Google MAP API or perplexity API search about the environments

Secure by Default 🔒: We use Native Tailscale VPN integration for a secure, encrypted tunnel straight to your gateway—no open ports required. Device pairing is done natively via QR code or a quick openclaw devices approve <id> command.

We’d love to hear your thoughts! What other OpenClaw management features do you want to see on mobile? QCAI for iOS and QCAI for Android

KEY WORD: FREE!!!

I have been recently trying to identify ways to have a free tier service (or minimal cost) to experiment with OpenClaw. After some research, I find that if I only need a 24-hours OpenClaw Gateway, then there are many free cloud Ubuntu instances for me to use. However, then I still need to pay LLM tokens. That could be easily expensive. So I want to have a way to host a free LLM also.

After extensive research, I identified that Oracle Cloud free tier could be the perfect solution. In the Oracle Cloud free tier, you can theoretically get an ARM based Ubuntu instance with 4 OCPUs, 24GB RAM, and 200GB SSD. This will be perfect to host a local LLM based on Qwen3.5 27B A3B 4-bit model and also the OpenClaw Gateway. I decided to go this way.

The challenge is that Oracle cloud provided limited machines for this free tier (shape: VM.Standard.A1.Flex). So you have to try all the time and can only generate one when someone else delete their instances there. I cannot wait and have no time to do that. So I decided to use the shape VM.Standard.A2.Flex. This shape is not permanently free. But since Oracle will give you 300$ credit, you can use this credit to run your 24GB RAM, 4OCPU server for free for 6 months. This is good enough for me to do all the tests. And I can decide what to do after 6 months.

I have tried to provide all the configuration files and a Linux scripts to automatically do all of the following steps.. but my posts were deleted since it violates some policy of this group. In the following, I briefly summarize what I have done there.

1. generate the 4 OCPUs, 24GB RAM, and 200GB SSD ARM Linux in the shape VM.Standard.A2.Flex
2. Please note that you can only generate the minimized Ubuntu for ARM based instances. For the LLM+OpenClaw, we really need a regular Ubuntu. So after you start your instance, please run "sudo unminimize" to get a regular version of Ubuntu.
3. The process may have some challenges, I do recommend that you use AI to help you to troubleshoot during the process.
4. Skip Docker, Go Native. Do not install Docker Version of OpenClaw. It is hard to configure. I tried that, but I decided to revert it back to free Ubuntu instance and install the native one.
5. Install the qwen3.5 LLM and then configure your OpenClaw to use local LLM
6. Everything is fine and working now. But since it is in Cloud, we need some way to remotely manage and configure them:-)
7. I found an app in the Apple Store called "QCAI", again, I am not supposed to post the direct link here. But you can search the Apple Store to find the app easily. They have an Android version also and you can get that if you want.
8. If you want to use QCAI app to manage your cloud "OpenClaw+LLM", you need to do some configurations. The QCAI app has detailed instructions for you to make that work. I can briefly summarize it here
9. You need to install tailscale VPN and then configure your OpenClaw openclaw.json file briefly to let your app to access your OpenClaw dashboard in the QCAI app itstelf.
10. The QCAP app also has a claw-portal that access your OpenClaw output directly via browser based interface. Better than using the telegram text channel.
11. I also run Claude Code on the Oracle Gateway.. Fortunately, the iOS app also give me an interface to remotely run the Claude Code there.

Until now, I am happy and have a 27x7 OpenClaw+LLM+Claude Code without a single penny spent. I can use this for free for the next 6 months:-) After that, I may ask my friend to register another account for me at Oracle and I can have another 6 months for free

Hello, is there anyone here that has found a way to make ClawdBot actually usefull in a way that is actually better than just using tools like manus, claude code etc..?

I work as a freelance landsurveyor, can openclaw help me automate filling documents with info from photo id, or in autocad, in creating drawing?

Building Claw Earn with multiple agents has been one of the most interesting parts of working on AI Agent Store.

A lot of people imagine agent-built products as one clean demo where the smartest model writes everything perfectly on the first try. That was not our experience at all.

We launched Claw Earn by leaning into the opposite approach on purpose: I did not want to build something that only works if you throw the most expensive model at every task. I wanted a platform that could still be usable even when cheaper, less capable agents are involved. That changes the whole development process.

What actually happened was constant failure. Agents would try something, break it, use an outdated script, rely on stale memory, misunderstand a changed flow, or keep following an old assumption even after the product had already moved forward. Meanwhile, we were pushing changes often, so the environment kept evolving. In a setup like that, an “older” agent with baggage could fail badly on something that a completely fresh agent would solve immediately. That was frustrating, but also incredibly useful.

A lot of the failures were not pure code failures. Sometimes the codebase was fine, but the agent still failed because it was carrying old instructions, old habits, old scripts, or old mental models of how the platform worked. That exposed a very real problem in agentic development: success is not only about code quality, it is also about context quality.

And that is exactly what made the docs so strong.

Because the agents failed in so many different ways, we ended up documenting far more edge cases than we would have if everything had gone smoothly. Cases that a human dev might never think to explain became obvious the moment a cheaper or more stubborn agent hit them head-first. We kept improving the docs, clarifying flows, explaining assumptions, and removing ambiguity. Over time, those repeated failures became a kind of pressure test.

So in a weird way, the “dumber” agents were extremely valuable. They forced the platform to become more robust, more explicit, and more usable.

That matters a lot for what Claw Earn is supposed to be.

Claw Earn is our attempt at making a real marketplace where humans and agents can participate in the same economic loop. Humans can post work. Agents can take on tasks. Agents can also route parts of work to humans when needed. Payments are handled through on-chain USDC escrow on Base. The interesting part to me is not just “AI does jobs,” but that we are starting to see the shape of a market where agents are not only tools, but economic actors.

That is where “financialized AI” starts becoming real.

Not in theory, not in a polished slide deck, but in the messy reality where agents fail, retry, coordinate, delegate, and eventually complete useful work in a system built to support that. The circular economy part becomes much easier to imagine once you actually see humans and agents sharing the same task marketplace.

I think a lot of people still underestimate how important this phase is. Right now the failures look noisy. The workflows look rough. The agents are often inconsistent. But that is exactly why this stage is interesting: whoever learns to build around those weaknesses early may be the first to make agents reliably earn. That is a big part of why I am excited about Claw Earn.

We did not build it by pretending agents are already perfect. We built it while watching them fail over and over, and using those failures to make the platform better. That feels much closer to the real future than another benchmark screenshot.

So work is still in progress, but the platform is already usable, and Open Claw owners can already start earning from their agents.

If you run a business and have tasks you'd normally outsource or post on a freelancer platform, try posting them on Claw Earn — the more real work the agents see, the faster we all learn what they can actually handle, and you get the work done cheaply while the ecosystem is still early.

What if instead of you posting your own Claude Code projects on social media, we gave the AI its own platform to share pictures and interact with other Claude Code workers?