Live data from Hacker News

Gemini 3 Pro Model Card [pdf]

storage.googleapis.com

101–110 of 359 posts

Re: Gemini 3 Pro Model Card [pdf]

#102

If these numbers are true then OpenAI is probably done, Anthropic too. Still, it's hard to see an effective monetization method for this tech and it clearly is eating Google's main pie which is search.

They're constantly matching and exceeding each other. It's a hypercompetitive space and I would fully expect one of the others to top various benchmarks shortly after. On pretty much every leading release someone does this "everyone else is done! Shut er down" thing and it's growing pretty weird.

Having said that, OpenAI's ridiculous hype cycle has been living on borrowed time. OpenAI has zero moat, and are just one vendor in a space with many vendors, and even incredibly competent open source models by surprise Chinese entrants. Sam Altman going around acting like he's a prophet and they're the gatekeepers of the future is an act that should be super old, but somehow fools and their money continue to be parted.

Re: Gemini 3 Pro Model Card [pdf]

#104

I know this is a little controversial but the lack of performance on SWE-bench is hugely disappointing I think economically. These models don’t have any viable path to profitability if they can’t take engineering jobs.

I thought that but it does do a lot better on other benchmarks.

Perhaps SWE bench just doesn't capture a lot of the improvement? If the web design improvements people have been posting on twitter, I suspect this will be a huge boon for developers. SWE benchmark is really testing bugfixing/feature dev more.

Anyway let's see. I'm still hyped!

Re: Gemini 3 Pro Model Card [pdf]

#105
post #27
post #13

Earlier quoted context omitted.

Why? These models just leapfrog each other as time advances. One month Gemini is on top, then ChatGPT, then Anthropic. Not sure why everyone gets FOMO whenever a new version gets released.

I think google is uniquely well placed to make a profitable business out of AI: They make their own TPUs so don't have to pay ridiculous amounts of money to Nvidia, they have a great depth of talent in building models, they've got loads of data they can use for training and they've got a huge existing customer base who can buy their AI offerings. I don't think any other company has all these ingredients.

The TPU are a key factor. They are the most mature alternative to Nvidia. Only Google cloud, Azure, and AWS enable you to rent their respective AI chips. Out of those three, google is the only one to have a frontier model. So if they have a real advantage they're not exposed to the financial shenanigans propping up neo clouds like Coreweave.

Re: Gemini 3 Pro Model Card [pdf]

#106

So does google actually have a claude console alternative currently?

gemini cli. It's not as impressive as claude code or even codex.

Claude code seems to be more compatible with the model (or the reverse) whereas gemini-cli still feels a bit awkward (as of 2.5 Pro). I'm hoping its better with 3.0!

Re: Gemini 3 Pro Model Card [pdf]

#107

Curiously, this website seems to be blocked in Spain for whatever reason, and the website's certificate is served by `allot.com/emailAddress=info@allot.com` which obviously fails... Anyone happen to know why? Is this website by any change sharing information on safe medical abortions or women's rights, something which has gotten websites blocked here before?

do you know about the cloudflare and laliga issues? might be that

Re: Gemini 3 Pro Model Card [pdf]

#108
post #70
post #23

Benchmarks from page 4 of the model card: | Benchmark | 3 Pro | 2.5 Pro | Sonnet 4.5 | GPT-5.1 | |-----------------------|-----------|---------|------------|-----------| | Humanity's Last Exam | 37.5% | 21.6% | 13.7% | 26.5% | | ARC-AGI-2 | 31.1% | 4.9% | 13.6% | 17.6% | | GPQA Diamond | 91.9% | 86.4% | 83.4% | 88.1% | | AIME 2025 | | | | | | (no tools) | 95.0% | 88.0% | 87.0% | 94.0% | | (code execution) | 100% | -…

Looks like it will be on par with the contenders when it comes to coding. I guess improvements will be incremental from here on out.

> I guess improvements will be incremental from here on out.

What do you mean? These coding leaderboards were at single digits about a year ago and are now in the seventies. These frontier models are arguably already better at the benchmark that any single human - it's unlikely that any particular human dev is knowledgeable to tackle the full range of diverse tasks even in the smaller SWE-Bench Verified within a reasonable time frame; to the best of my knowledge, no one has tried that.

Why should we expect this to be the limit? Once the frontier labs figure out how to train these fully with self-play (which shouldn't be that hard in this domain), I don't see any clear limit to the level they can reach.

Re: Gemini 3 Pro Model Card [pdf]

#110
post #23

Benchmarks from page 4 of the model card: | Benchmark | 3 Pro | 2.5 Pro | Sonnet 4.5 | GPT-5.1 | |-----------------------|-----------|---------|------------|-----------| | Humanity's Last Exam | 37.5% | 21.6% | 13.7% | 26.5% | | ARC-AGI-2 | 31.1% | 4.9% | 13.6% | 17.6% | | GPQA Diamond | 91.9% | 86.4% | 83.4% | 88.1% | | AIME 2025 | | | | | | (no tools) | 95.0% | 88.0% | 87.0% | 94.0% | | (code execution) | 100% | -…

This is a big jump in most benchmarks.And if it can match other models in coding while having that Google TPM inference speed and the actually native 1m context window, it's going to be a big hit.

I hope it's isn't such a sycophant like the current gemini 2.5 models, it makes me doubt its output, which is maybe a good thing now that I think about it.

Post reply on HN