I was late to AI coding tools. Skeptical, honestly.
Then I tried Claude Code and Cursor. Hit the $100/month mark, ran out of credits in two weeks.
That's when I stopped paying for subscriptions and started building my own stack from open-source tools and dirt-cheap Chinese models.
Here's what I actually use every day—and why it works better than the paid stuff.
1. Dev Containers (VS Code's Secret Weapon)
VS Code's Dev Containers changed how I work completely. Spin up a containerized dev environment on any platform—no "works on my machine" nonsense.
Here's what nobody talks about: your AI context, MCP servers, autocomplete—all of it works inside the container exactly like it does locally.
// .devcontainer/devcontainer.json
{
"name": "My Project",
"image": "mcr.microsoft.com/devcontainers/base:ubuntu",
"features": {
"ghcr.io/devcontainers/features/node:1": {}
},
"customizations": {
"vscode": {
"extensions": ["continue.continue", "github.copilot"]
}
}
}
Python ML project → Node.js API → Rust debugging? One click, new container, full AI support. No subscription needed.
2. Devstral 2 for Autocomplete (Mistral's Free Gift)
Mistral released Devstral 2 with genuinely generous free limits. Thousands of completions per day. Completely free.
Fast, accurate, doesn't try to rewrite your entire function when you just need the next line.
GitHub Copilot: $10/month.
Devstral 2: Free.
3. OpenRouter Chat + Hugging Face (My Model Testing Lab)
Before I commit to using a model for a big project, I test it.
OpenRouter Chat is my playground. Same prompt → Claude, GPT-4, DeepSeek, Gemini, Qwen → see which one actually gets the job done. I was building a Rust learning app, needed terminal UI code. Tested five models in ten minutes. DeepSeek won. Cost me pennies.
Hugging Face is where I go deeper. Leaderboards, benchmark comparisons, fine-tuning on my own data.
When prepping for Tech Lead interviews, I fine-tuned a smaller model on system design scenarios. Ran it locally, completely private, no API costs.
This combo is how you figure out which LLM can do your specific job for a fraction of the price.
4. Antigravity IDE + MCP Servers (Google's Productivity Monster)
Google's Antigravity IDE has built-in MCP integrations—Notion, entire G Suite, Context7, all preconfigured.
Generous Gemini limits: thousands of requests per day on free tier. That's $100+/month of access with other providers.
When I tell the AI "summarize this week's meeting notes and update the roadmap"—it reads my calendar, pulls Drive docs, updates Notion, creates follow-up tasks.
Most underrated MCP servers:
| Server | What It Does |
|---|---|
| Rube (ComposioHQ) | Connects 100+ SaaS tools with one integration |
| Github | Read repos, create PRs, review code in-IDE |
| Firecrawl | Scrapes and structures web content for context |
| Context7 | Unified search across all your docs |
| YepCode | Serverless functions from your prompts |
5. Chinese Open-Source Models (The Price-Performance Champions)
This is where the paid AI market got disrupted. Frontier-quality, almost nothing in cost.
| Model | Context | Input Price | Output Price | Best For |
|---|---|---|---|---|
| GLM-4.7 | 128K | $0.60/M | $2.20/M | Long context coding |
| MiniMax M2.1 | 4M | $0.30/M | $1.20/M | Agent workflows |
| DeepSeek R1 | 64K | $0.14/M | $0.56/M | All-around best value |
| Qwen VL | 32K | $0.09/M | $0.30/M | Vision tasks |
| FLUX.2 Klein 8B | N/A | Free (local) | Free (local) | Image gen in <1 second |
Why so cheap? Mixture of Experts architecture, cheaper Chinese GPUs, market share > profit.
Performance? I've run the same tasks on Claude Sonnet and DeepSeek. Can't tell the difference.
6. Obsidian + Agent Skills (Second Brain, Supercharged)
My second brain lives in Obsidian. Articles, research notes, ideas.
I created Agent Skills that connect to my vault. Now when researching, the AI has context on everything I've saved. Surfaces related notes I forgot about, suggests connections between ideas.
Agent Skills aren't just for coding:
- Learning workflows (study plans, resource tracking)
- Research (summarizes papers, finds gaps)
- Career development (tracks skills, suggests paths)
Your Obsidian vault becomes the knowledge base. Agent Skills become the interface. You're not starting from zero every time.
7. Claude Code Extension + Excalidraw (Visual Thinking, Fast)
The Claude Code Chrome extension lets me create visuals in Excalidraw without leaving my browser.
Need a system architecture diagram? Describe it → Claude generates Excalidraw code → paste → clean diagram.
Faster than Miro, cheaper than Lucidchart.
8. Bonus: Almost-Free Tools
Free LLMs: Xiaomi's MiMo-V2-Flash, BigPickle, Grok-code-1, Devstral Small 2, GLM-4.7-flash
Kilo Code: Free $20 credits on signup
n8n: Open-source workflow automation. Self-host for free.
Google AI Studio: 1,000-1,500 requests/day free, 500K+ TPM
Mistral AI: Several models completely free via API
The pattern? Every paid tool has a free or dirt-cheap alternative.
Who This Actually Helps
Developers where $100-200/month for AI tools is real money.
Indie hackers juggling side projects.
Students who can't expense subscriptions.
Anyone stacking Cursor + Claude + Midjourney + ChatGPT watching bills pile up.
I'm not rationing AI anymore. I built that Rust learning app because I wanted to—not because it was "important enough" to justify credits.
The psychological shift from "is this worth spending tokens on?" to "let me just build it" is massive.
The Bottom Line
The free alternatives are good enough now. The only thing stopping you is not knowing they exist.
Now you know.
What's in your AI stack? Drop your favorite free tools in the comments—I'm always looking for new discoveries.
Top comments (2)
This is a really solid breakdown — especially the part about the psychological shift from “is this worth tokens?” to “just build it.” That hit home.
I like how practical this is. No hype, no “$200/month stack” — just tools that actually get work done. The Chinese models + OpenRouter combo is something more people should be experimenting with instead of defaulting to one paid tool.
Also +1 on Dev Containers. Once your AI + tooling lives inside the container, it’s hard to go back.
Curious: if you had to recommend just one free setup for a beginner starting today, what would you pick first?
Good Question!
Google's Antigravity + NotebookLM is the way to go if you are a beginner (if you wanna go paid, I'd still suggest this setup)
Why?