Relevant: Scanned diaries from 1945 of USFS Ranger. Had this transcribed in Claude.

[1]:https://news.ycombinator.com/item?id=47041836

Gemini 3 was:

1. unreliable in GH copilot. Lots of 500 and 4XX errors. Unusable in the first 2 months

2. not available in vertex ai (europe). We have requirements regarding data residency. Funny enough anthropic is on point with releasing their models to vertex ai. We already use opus and sonnet 4.6.

I hope google gets their stuff together and understands that not everyone wants/can use their global endpoint. We'd like to try their models.

I asked Gemini 3.1 Pro to generate some of the modern artworks in my "Pelican Art Gallery". I particularly like the rendition of the Sunflowers: https://pelican.koenvangilst.nl/gallery/category/modern

I use gemini if i need to write something in my native language- Malayalam or translation. it works very well in writing in Indian regional languages.

I've been playing with the 3.1 Deep Think version of this for the last couple of weeks and it was a big step up for coding over 3.0 (which I already found very good).

It's only February...

77.1% on ARC-AGI-2 and still can't stop adding drive-by refactors. ARC-AGI-2 tests novel pattern induction, it's genuinely hard to fake and the improvement is real. But it doesn't measure task scoping, instruction adherence, or knowing when to stop. Those are the capabilities practitioners actually need from a coding agent. We have excellent benchmarks for reasoning. We have almost nothing that measures reliability in agentic loops. That gap explains this thread.

Gets 10/10 on my potato benchmarks: https://aibenchy.com/model/google-gemini-3-1-pro-preview-med...

A lot of gemini bashing. But flash 3.0 with opencode is reasonably good and reliable coder.

I'd rate it between haiku 4.5 (also pretty good for a price) and sonnet. Closer to sonnet.

Sure, if I am not cost-sensitive I'd run everything in opus 4.6 but alas.

One underappreciated reason for the agentic gap: Gemini tends to over-explain its reasoning mid-tool-call in a way that breaks structured output expectations. Claude and GPT-4o have both gotten better at treating tool calls as first-class operations. Gemini still feels like it's narrating its way through them rather than just executing.