[rhubarbtree]

Google are stuck because they have to compete with OpenAI. If they don’t, they face an existential threat to their advertising business.

But then they leave the door open for Anthropic on coding, enterprise and agentic workflows. Sensibly, that’s what they seem to be doing.

That said Gemini is noticeably worse than ChatGPT (it’s quite erratic) and Anthropic’s work on coding / reasoning seems to be filtering back to its chatbot.

So right now it feels like Anthropic is doing great, OpenAI is slowing but has significant mindshare, and Google are in there competing but their game plan seems a bit of a mess.

[frogperson]

Google might be a mess now, but they have time. OpenAI and Anthropic are on barrowed time, Google has a built in money printer. They just need to outlast the others.

[harrall]

Plus they started making AI processors 11 years ago and invented the math behind “GPTs” 9 years ago. Gemini is way cheaper to run for them than it does for everyone else.

I think Gemini is really built for their biggest market — Google Search. You ask questions and get answers.

I’m sure they’ll figure out agentic flows. Google is always a mess when it comes to product. Don’t forget the Google chat sagas where it seems as if different parts of the company were making the same product.

[seg_lol]

They have much much less time than one would think. Their ads business is about to go into freefall, this will cause the whole company to spiral.

[holoduke]

Google is Google. Too much restrictions on the model output. Ask it to create a pentest or let it request a pub key for ssh access and it will refuse.

[tempestn]

In my experience Gemini 3.0 pro is noticeably better than chatgpt 5.2 for non-coding tasks. The latter gives me blatantly wrong information all the time, the former very rarely.

[user34283]

I agree and it has been my almost exclusive go to ever since Gemini 3 Pro came out in November.

In my opinion Google isn't as far behind in coding as comments here would suggest. With Fast, it might already have edited 5 files before Claude Sonnet finished processing your prompt.

There is a lot of potential here, and with Antigravity as well as Gemini CLI - I did not test that one - they are working on capitalizing on it.

[pants2]

Strange that you say that because the general consensus (and my experience) seems to be the opposite, as well as the AA-Omniscience Hallucination Rate Benchmark which puts 3.0 Pro among the higher hallucinating models. 3.1 seems to be a noticeable improvement though.

[b3ing]

Google is good for answering questions but its writing is lacking. I’ve had to deal with Gemini slop and it’s worse than ChatGPT

[da_chicken]

I would agree that Gemini is not keeping up with Anthropic on coding, but I completely disagree on ChatGPT. It's been months for me since I've gotten anything from OpenAI that felt like it was worth my time. I don't really consider them anymore.

Google is mostly doing what they've always done. They've created a few tools like Gemini and NotebookLM, and they're going to focus more effort on whatever gets the most traffic. Then anything they can't monetize will get cut.

[jacquesm]

Google is scoring one own goal after another by making people working with their own data wonder how much of that data is sent off to be used to train their AI on. Without proof to the contrary I'm going to go with 'everything'.

They should have made all of this opt-in instead of force-feeding it to their audience, which they wrongly believe to be captive.

[bluegatty]

Yup, you got it. It's a weird situation for sure.

You know what's also weird: Gem3 'Pro' is pretty dumb.

OAI has 'thinking levels' which work pretty well, it's nice to have the 'super duper' button - but also - they have the 'Pro' product which is another model altogether and thinks for 20 min. It's different than 'Research'.

OAI Pro (+ maybe Spark) is the only reason I have OAI sub. Neither Anthropic nor Google seem to want to try to compete.

I feel for the head of Google AI, they're probably pulled in major different directions all the time ...

[visarga]

If you want that level of research I suggest you ask the model to draft a markdown plan with "[ ]" gates for todo items, and plan it in as many steps as needed. Then ask another LLM to review the plan, judge it. In the end use the plan as the execution state tracker, the model solves one by one the checkboxes.

Using this method I could recreate "deep research" mode on a private collection of documents in a few minutes. A markdown file can be like a script or playbook, just use checkboxes for progress. This works for models that have file storage and edit tools, which is most, starting with any coding agent.

[jswny]

Can you explain what’s so different about pro?

I’ve used everything frontier model and had Pro a while ago but it seemed to just be the same models served faster at the time.

[dakolli]

They all suck!!!