It's not just LLM sourced though, folks have literally tried this after the release with the 26A4B model and it wasn't very good. Maybe the dense ~31B model is worthwhile though.

Many Gemma implementations are or were broken on launch day. The first attempts to fix llama.cpp’s tokenizer were merged hours ago.

Everyone hated Qwen3.5 at launch too because so many implementations were broken and couldn’t do tool calling.

You need to ignore social media “I tried this and it sucks” echo chambers for new model releases.

I agree with your criticism. I should have simply said that I had good results with gemma 4 tool use, and agentic coding with gemma 4 didn’t yet work well for me.

I spent two hours doing my own research before asking for Gemini’s analysis, which reinforced my own opinion that the gemini models historically have not been trained and target for agentic coding use.

Have you tried using the new Gemma 4 models with agentic coding tools?If you do, you might end up agreeing with me.

I've found my research on certain topics like this becoming less reliable these days, compared to just trying it out to form an opinion.

I wasn’t very clear, sorry. By my ‘own research’ I meant spending 90 minutes experimenting with Gemma 4 models for tool use (good results!) and a half hour using with pi and OpenCode (I didn’t get good results, yet.)

LLMs can search the web. Although I don’t trust the LLM (or someone repeating its claim) without quotes and URLs to where it got the information.