These announcements have started to look like a template.

- Our state-of-the-art model.

- Benchmarks comparing to X,Y,Z.

- "Better" reasoning.

It might be an excellent model, but reading the exact text repeatedly is taking the excitement away.

I’m sure the AI helps write the announcements.

I wonder what about this one gets the +0.5 to the name. IIRC the 2.0 model isn’t particularly old yet. Is it purely marketing, does it represent new model structure, iteratively more training data over the base 2.0, new serving infrastructure, etc?

I’ve always found the use of the *.5 naming kinda silly when it became a thing. When OpenAI released 3.5, they said they already had 4 underway at the time, they were just tweaking 3 be better for ChatGPT. It felt like a scrappy startup name, and now it’s spread across the industry. Anthropic naming their models Sonnet 3, 3.5, 3.5 (new), 3.7 felt like the worst offender of this naming scheme.

I’m a much bigger fan of semver (not skipping to .5 though), date based (“Gemini Pro 2025”), or number + meaningful letter (eg 4o - “Omni”) for model names.

I would consider this a case of "expectation management"-based versioning. This is a release designed to keep Gemini in the news cycle, but it isn't a significant enough improvement to justify calling it Gemini 3.0.

At least for OpenAI, a .5 increment indicates a 10x increase in training compute. This so far seems to track for 3.5, 4, 4.5.

I think it's because of the big jump in coding benchmarks. 74% on aider is just much, much better than before and worthy of a .5 upgrade.

Agreed, can't everyone just use semantic versioning, with 0.1 increments for regular updates?

I'm most impressed by the improvement on Aider Polyglot; I wasn't expecting it to get saturated so quickly.

I'll be looking to see whether Google would be able to use this model (or an adapted version) to tackle ARC-AGI 2.

I wish they’d mention pricing - it’s hard to seriously benchmark models when you have no idea what putting it in production would actually cost.

The Long Context benchmark numbers seem super impressive. 91% vs 49% for GPT 4.5 at 128k context length.

Google has the upperhand here because they are not dependent on nvidia for hardware. They make and uses their own AI accelerators.

Isn't every new AI model the "most "?

Nobody is going to say "Announcing Foobar 7.1 - not our best!"

GPT-4.5's announcement was the equivalent of that.

"It beats all the benchmarks...but you really really don't want to use it."

They even priced it so people would avoid using it. GPT-4.5's entire function was to be the anchor of keeping OpenAI in the news, to keep up the perception of releasing quickly.

Except for GPT 4.5 and Claude 3.7 :/

gobble 2.0 - a bit of a turkey

> This will mark the first experimental model with higher rate limits + billing. Excited for this to land and for folks to really put the model through the paces!

From https://x.com/OfficialLoganK/status/1904583353954882046

The low rate-limit really hampered my usage of 2.0 Pro and the like. Interesting to see how this plays out.

Slight tangent: Interesting that they use o3-mini as the comparison rather than o1.

I've been using o1 almost exclusively for the past couple months and have been impressed to the point where I don't feel the need to "upgrade" for a better model.

Are there benchmarks showing o3-mini performing better than o1?

I noticed this too, I have used both o1 and o3 mini extensively, and I have ran many tests on my own problems and o1 solves one of my hardest prompts quite reliably but o3 is very inconsistent. So from my anecdotal experience o1 is a superior model in terms of capability.

The fact they would exclude it from their benchmarks seems biased/desperate and makes me trust them less. They probably thought it was clever to leave o1 out, something like "o3 is the newest model lets just compare against that", but I think for anyone paying attention that decision will backfire.

I find o3 at least faster to get to the response I care about, anecdotally.

why not enable Canvas for this model on Gemini.google.com? Arguably the weakest link of Canvas is the terrible code that Gemini 2.0 Flash writes for Canvas to run..