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"create a svg of a unicorn playing xbox"
https://www.svgviewer.dev/s/NeKACuHj
Still some tweaks to the final result, but I am guessing with the ARC-AGI benchmark jumping so much, the model's visual abilities are allowing it to do this well.
For conversational contexts, I don't think the (in some cases significantly) better benchmark results compared to a model like Sonnet 4.6 can convince me to switch to Gemini 3.1. Has anyone else had a similar experience, or is this just a me issue?
Anthropic is clearly targeted to developers and OpenAI is general go to AI model. Who are the target demographic for Gemini models? ik that they are good and Flash is super impressive. but i’m curious
Earlier quoted context omitted.
The touted SVG improvements make me excited for animated pelicans.
I just gave it a shot and this is what I got: https://codepen.io/takoid/pen/wBWLOKj The model thought for over 5 minutes to produce this. It's not quite photorealistic (some parts are definitely "off"), but this is definitely a significant leap in complexity.
Does well on SVGs outside of "pelican riding on a bicycle" test. Like this prompt: "create a svg of a unicorn playing xbox" https://www.svgviewer.dev/s/NeKACuHj Still some tweaks to the final result, but I am guessing with the ARC-AGI benchmark jumping so much, the model's visual abilities are allowing it to do this well.
I always try Gemini models when they get updated with their flashy new benchmark scores, but always end up using Claude and Codex again... I get the impression that Google is focusing on benchmarks but without assessing whether the models are actually improving in practical use-cases. I.e. they are benchmaxing Gemini is "in theory" smart, but in practice is much, much worse than Claude and Codex.
Gemini can go off the rails SUPER easily. It just devolves into a gigantic mess at the smallest sign of trouble.
For the past few weeks, I've also been using XML-like tags in my prompts more often. Sometimes preferring to share previous conversations with `` and `` tags. Opus/Sonnet handles this just fine, but Gemini has a mental breakdown. It'll just start talking to itself.
Even in totally out-of-the-ordinary sessions, it goes crazy. After a while, it'll start saying it's going to do something, and then it pretends like it's done that thing, all in the same turn. A turn that never ends. Eventually it just starts spouting repetitive nonsense.
And you would think this is just because the bigger the context grows, the worse models tend to get. But no! This can happen well below even the 200.000 token mark.
I hope to have great next two weeks before it gets nerfed.
Pretty great pelican: https://simonwillison.net/2026/Feb/19/gemini-31-pro/ - took over 5 minutes though, but I think that's because they're having performance teething problems on launch day.
I hereby allow you to release models not at the same time as your competitors.