One open source tool. $10 a month. I found out what the rest of the AI landscape can actually do.
Most people use one AI provider. Not because they chose the best one, but because trying anything else is a hassle.
Different tools, different accounts, different subscriptions. Each model locked behind its own ecosystem. So you stick with what you know.
I use AI tools like Anthropic's Claude Code or Google's Gemini CLI every day. They are excellent and I am not replacing them. But I grew curious about the alternatives that have been gaining ground on the established players. The friction of actually trying them kept me from exploring.
Separately, I have been using OpenCode for a while now. It is an AI coding assistant like the ones from Anthropic or Google, but fully open source and model-agnostic: one interface, any AI model you want, including models running on your own machine. I started using it because I wanted a tool I could inspect and control, not another black box. It was rough around the edges early on, but the project has matured considerably: a desktop app, a web interface, extensions for all major code editors, and much better handling of long work sessions.
Recently, I discovered OpenCode Go. And it connected both threads.
For $10 a month, you get access to a roster of models through a single subscription. No juggling tools or accounts. Just one place to see what the rest of the AI landscape can actually do.
What I found surprised me. DeepSeek V4 Pro is producing code at a level that required a premium subscription to Anthropic or Google a year ago. Kimi K2.6 handles long, complex coding sessions. Planning, writing, testing, debugging in sequence, with a consistency I did not expect. And they are not the only ones in the roster. These are not theoretical benchmark results. This is what I see in my actual daily work. Not just coding, but research, writing, and strategic planning.
One thing I want to be honest about. The models in OpenCode Go are "open-weight", not open source. That means the trained model is publicly released for anyone to download and use, but the training data and process behind it typically are not. Some, like DeepSeek V4, use permissive licenses with no restrictions on commercial use. Others come with conditions worth reading before you build on them. OpenCode itself is fully open source. And if you prefer nothing leaving your machine, you can run your own models locally instead.
If you have been curious about AI beyond the usual names but the friction of actually trying them held you back: that barrier is largely gone. OpenCode Go is probably the lowest-effort way to find out for yourself.
