You know that moment when you look at your credit card statement and realize you're spending more on AI subscriptions than on your Netflix + Spotify + gym membership combined?
Yeah. That was me last month.
I was paying $70 a month — GitHub Copilot ($10), ChatGPT Plus ($20), Claude Pro ($20), and Cursor Pro ($20). And honestly? I wasn't even sure I was getting $70 worth of value. So I did something drastic. I cancelled all of them and decided to see if 2026's local AI scene could actually replace my entire subscription stack.
Spoiler: the answer is... complicated. But probably not in the way you'd expect.
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AI-generated illustration: futuristic AI data flow visualization section
The Breaking Point
Here's the thing — I don't hate these tools. Claude is genuinely brilliant at reasoning tasks. Cursor's inline editing is slick as hell. GitHub Copilot has saved me from writing boilerplate more times than I can count.
But $70/month adds up to $840 a year. That's a new monitor. That's six months of domain renewals. That's... a lot of money for tools that mostly do the same thing with different interfaces.
I started asking around in some dev Discord servers (shoutout to the r/LocalLLaMA crew), and I realized something: the local AI landscape has changed massively in the last year. We're not in 2024 anymore, where running a model locally meant either a 7B parameter model that couldn't write a working FizzBuzz or needing a 400W GPU that sounded like a jet engine.
What I Actually Set Up
My rig is pretty modest — a 2023 MacBook Pro with 32GB of RAM. No fancy RTX 4090. No external GPU enclosure. Just what I already owned.
Here's my setup:
- Ollama as the model runner (it's free, open-source, and stupidly easy to use)
- Continue.dev as the VS Code extension (connects to Ollama and gives me Copilot-style autocompletions)
- Gemma 4 9B for day-to-day coding (it's Apache 2.0 licensed, runs great on 32GB, and Google's been putting serious work into it)
- Llama 3.2 8B as my fallback for when I want something different
- Mistral Small 3 for lightweight tasks — this thing runs at like 50 tokens/second on an M-series chip
- Open WebUI as a ChatGPT replacement frontend (also free, also amazing)
Total cost: $0. Just electricity.
What Actually Works Well
Code Completions Are Surprisingly Good
I'll be honest — I expected this to be the thing that made me run back to Copilot with my tail between my legs. But Continue.dev + Gemma 4 9B has genuinely impressed me. It's not as fast as Copilot's inline completions (there's a slight ~1-2 second delay), but the suggestions are thoughtful. It understands my project context because it's running locally and has access to my full workspace.
I've found it actually catches more project-specific patterns than Copilot did, because Copilot's cloud model can't see my entire codebase the way a local model can when Continue points it at my open files.
Chat Assistance Where I Actually Own My Data
This is the part I didn't expect to care about but now I can't go back. When I ask Open WebUI a question about my code, nothing leaves my machine. No prompts being analyzed. No code snippets being cached on some server farm. No worrying about whether I'm accidentally sending proprietary code through an API.
After reading that article about the "transfer station economy" where people's prompts and code logs are being scraped through API proxies — yeah, I'm way more comfortable with everything staying on my laptop.
The Speed Trade-Off Is Smaller Than I Thought
| Task | Cloud (GPT-4/------) | Local (Gemma 4 9B) |
|---|---|---|
| Code generation | 1-3s | 3-8s |
| Code completion | ~0.5s | 1-2s |
| Debug help | 2-5s with reasoning | 5-12s |
| Explaining a concept | 3-8s | 5-15s |
| Refactoring a function | 2-4s | 4-10s |
Yeah, it's slower. But not annoyingly slower. It's the difference between "instant" and "give it a few seconds." And honestly, I kind of prefer the slight pause — it gives me time to think about the suggestion instead of blindly tab-completing everything.
Where Local Still Falls Short
I'm not going to sugarcoat this. there're things I genuinely miss.
Complex reasoning tasks are still a weak point. If I need to analyze a 5,000-line codebase architecture and suggest a refactoring strategy, I'm reaching for Claude. Local models just don't have the context window depth for really gnarly problems. Not yet, anyway.
Multimodal stuff is hit or miss. Gemma 4 can handle images, but it's slower and less accurate than GPT-4o at reading screenshots or diagrams. If your workflow involves a lot of "here's a screenshot of this bug, what's wrong?" — you'll feel the difference.
The setup friction is real, even if it's getting better. Getting Open WebUI working with Ollama took me about 45 minutes of fiddling. Getting Continue.dev configured the way I wanted — with the right model, the right context settings, the right keybindings — was another hour. Compare that to installing Cursor and having it work immediately.
The Verdict After 3 Weeks
I've been running fully local for 21 days now. Here's my honest take:
I'm keeping the local setup. But I'm not completely unsubscribed.
What I actually did was drop Copilot ($10) and Cursor ($20) — Continue.dev + Ollama replaced both of those without me feeling the loss. I kept Claude Pro ($20) as my "I need serious reasoning help" fallback, and I dropped ChatGPT Plus because Claude already filled that role better for my use case.
So my monthly spend went from $70 to $20. And honestly, I use Claude less than I used to, because the local setup handles 80% of my daily needs. I might drop Claude too next month — we'll see.
Disclosure: Some of the links in this article are affiliate links. If you purchase through them, I may earn a commission at no extra cost to you. I only recommend products I genuinely find useful.
Bottom Line
If you've been wondering whether local AI is "ready" in 2026 — it's. Not for everything, but for the vast majority of what developers actually do day-to-day (writing code, debugging, asking questions about APIs, getting explanations), the local experience is genuinely good enough.
The real win isn't even the money. It's the ownership. Knowing my code stays on my machine. Not worrying about rate limits. Being able to use any model I want without paying per token. And honestly — it just feels more fun. There's something satisfying about knowing the AI assistant running in your editor is running on your hardware, answering your questions, without a middleman.
That said, if you're doing heavy architecture work or need advanced reasoning every day, keep your Claude subscription. I did. The local/cloud hybrid approach — local for daily coding, cloud for the hard stuff — is honestly the best of both worlds.
Try it. Ollama takes five minutes to install and you can have a model running before you finish your coffee. Worst case, you're back to your subscriptions with a new appreciation for what $70/month actually buys you.
I write about AI tools, developer productivity, and the local AI movement. Follow me for more experiments like this one.
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