I used to pay 30 dollars per month (per user!) for ChatGPT. Then I realized I could self-host the UI and save thousands 🤑
I replaced it all with a self-hosted setup using Open WebUI, and it is now saving me thousands of dollars a year across sliplane.io and side projects.
What is Open WebUI?
It is an open source, offline-first interface for local and remote LLMs. You can hook it up to:
- Ollama for local models like LLaMA, Mistral, or Phi-3
- OpenAI-compatible APIs like Mistral, Together, Groq, LM Studio, or LocalAI (and obviously OpenAI itself)
- Built-in RAG support with local files or vector databases
- A modern interface that feels very close to ChatGPT
You get most of ChatGPT without the recurring bill, and with (nearly) full control.
Here is what Open WebUI looks like in action:
The clean and familiar chat interface
Easy member management and settings
Built-in RAG (Retrieval Augmented Generation) support
Why I Switched
I used to pay for the ChatGPT Team plan. Thirty dollars per user per month. That adds up quickly if you are running a business or even a small team.
The truth is we did not need most of the Team features. We just wanted a clean interface, conversation history, and reliable model access. Open WebUI gave us exactly that, and for free.
My Setup
- Open WebUI hosted on Sliplane
- OpenAI API key for running models remotely (or locally with Ollama)
It runs in my existing infra, feels almost as good, and gives me more flexibility. You can of course run it on any server you want, I of course am slightly biased and will always use Sliplane :)
Run It with Docker
If you are just getting started, you can run it with a single command:
docker run -d -p 3000:8080 \
-e OPENAI_API_KEY=your_secret_key \
-v open-webui:/app/backend/data \
--name open-webui \
--restart always \
ghcr.io/open-webui/open-webui:main
Or use Docker Compose:
services:
open-webui:
image: ghcr.io/open-webui/open-webui:main
container_name: open-webui
ports:
- "3000:8080"
environment:
- OPENAI_API_KEY=your_secret_key
volumes:
- open-webui:/app/backend/data
restart: always
volumes:
open-webui:
Then open http://localhost:3000
in your browser.
Tradeoffs
Open WebUI gets surprisingly close to ChatGPT in features, but there are still some tradeoffs:
You manage the backend
You choose the model (OpenAI, Mistral, Ollama, etc.), which means you also manage latency, availability, and cost. Great flexibility, but more responsibility.Not everything is as seamless
While it has browsing and a code interpreter, they’re not always as tightly integrated or polished as in ChatGPT. Some tools require extra setup (like file system access or external APIs).Self-hosting comes with overhead
You’ll need to manage updates, API keys, and occasional debugging. It’s low maintenance once running, but still something to monitor.Team features are basic
It supports multiple users and conversations, but lacks more advanced enterprise features like role-based access, usage analytics, or granular billing (not super deep into the enterprise stuff but I am sure it is not as advanced as ChatGPT).
If you're okay with a little tinkering, Open WebUI gives you a huge amount of value and control in return.
Deploy It on Sliplane
Want the fastest way to get started without touching a server?
You can deploy Open WebUI on Sliplane in under 2 minutes:
- One click deploy
- HTTPS out of the box
- Secrets management built in
- Backups included
- Runs on European infrastructure
The Savings
Here is what the cost difference looked like for me:
Tool | Monthly cost per user | Users | Yearly cost |
---|---|---|---|
ChatGPT Team | 30 | 3 | 1080 |
Open WebUI | 3-5 | unlimited | 108 |
API | pay per use | shared | ~240 |
The cost for Open WebUI depends on the hosting you use, I put it on a Base Sliplane server, which costs 9 Euros per month. Assuming you don't have a team of 100 users that all use it concurrently this will be plenty of performance.
You then also pay for the API calls which depends on the model you use and the amount of requests you make, but I can guarantee you most users will never hit 30 dollars a month in usage :)
Final Thoughts
If you are
- Spending too much on AI tools
- Comfortable running Docker
- Fine with a few rough edges
Then self-hosting Open WebUI is one of the easiest wins out there. Combine it with a good API backend like Mistral or run models locally with Ollama, and you get most of what ChatGPT offers for a fraction of the cost.
It saved me thousands. Maybe it will do the same for you.
Cheers,
Jonas, Co-Founder of Sliplane
Top comments (10)
Thanks for the post.
I'm curious which models you're actually using with this setup. Are you using only self-hosted, open source models? Or are you using cheaper APIs through services like Open Router? I've found that, generally, sticking with only open source models led to inferior results for more complex tasks, so really interested to know more about your experience and your use cases.
Also, Open WebUI is technically not "open source" but rather "source available", since they changed their license from
BSD-3-Clause
toOpen WebUI License
.Oh yeah agree, for complex stuff the open source models aren’t great. I use open router extensively and switch between 5-10 models all the time depending on the task :D
I actually didn’t know about the license thing! In this case I care more about not paying OpenAI 30 bucks than it being truly open source, but I will add it to the post:)
Its really good as you can pick your own TTS, STT and emebdding models. Hooking it up to ComfyUI is the icing on the cake for me. Connecting it to things like Tavily and other advanced custom search fearures can get very very complicated though
Interesting! Haven't tried that yet. What did you connect ComfyUI for? Some more complex workflows?
Yes, if comfyui is running you can for example generate an animation capturing your idea and export that as a GIF/webm
Thanks for the good and informative post.
Love this! 🔥 Huge fan of taking control and cutting costs while still getting top-tier AI access...
Great post indeed!! :)
Good Post 🌟
Want to reduce code review cycles? Try adopting a style guide like this one:
rkoots.github.io/styleguide/
Some comments have been hidden by the post's author - find out more