This week, OpenAI released their open-weight (Apache 2 licensed) models gpt-oss-20b and gpt-oss-120b. IMO, this is bigger news than their other model release this week, GPT-5. The expert analyses are showing that the 120B and 20B models are very capable while being significantly smaller in parameters compared to the competition. Running an O4-mini or O3-mini level model in a consumer laptop would have been unimaginable a few weeks ago, but here we are.
The above video shows my experience running gpt-oss-20b on a 2024 M3 MacBook Air with LM Studio. Although the tokens generated per second are quite low, it is still usable. (Also, I've realized that LM-studio with its MLX support is much faster and far superior to Ollama in usability.) Here I'm getting the model to retrieve a live web page (BBC home page) and extract the news headings, all happening locally on a laptop with the help of a code sandbox and an MCP tool invoking playwright. 😅
Microsandbox and coderunner open up lots of possibilities here to make life easier using local models.
Talking about possibilities, Google also released Genie 3, which I believe will have many implications across video game development, filmmaking, robotics, and many other industries. Sadly, it didn't get the attention it deserved in my opinion.
Coding agents are the talk of the town these days. But interestingly, everyone (except Claude Code) is open-sourcing their product, it seems!
- Gemini CLI
- OpenAI codex CLI
- VSCode Copilot Chat
- Github Spark (not really open sourced. Reverse engineered, then later confirmed to be true.)
All in all, we may not be any closer to ASI or AGI. But the progress the field has achieved so far is big enough to change the trajectory of lots of careers (and economies too), I think. I wonder what new advancements we'll see in the coming months.
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