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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 th

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.

bluegatty 8mo ago
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 8mo ago
  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.
  - bluegatty 8mo ago
    OAI Pro is not a 'research' tool in that sense, and it's definitely different than the 'deep research' options avail on most platforms, as I indicated. It's a different kind of solution altogether. I suggest trying it.
    - luipugs 8mo ago
      It's a different kind of solution :)
- jswny 8mo ago
  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.
  - bluegatty 8mo ago
    It's a different model and designed to 'think very hard' about issues. It's basically a 'very extended thinking mixed with research' type of solution. While the 'research' solutions tend to go very wide and come back with a 'paper' the Pro model seems to do an exhaustive amount of thinking combined with research, and tries to integrate findings. I think it goes down a lot of rabbit holes. I find it's by far the best way to find solutions to hard problems, but it typically does require a 'hard problem' in order to shine. And it takes an enormous amount of time. Ito could be essentially a form of 'saturating the problem with tokens'. It's OAI's most expensive model by far. A prompt usually costs me $1-3 if paying per token.
  - szundi 8mo ago
    [dead]
jacquesm 8mo ago
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.
frogperson 8mo ago
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 8mo ago
  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.
  - LPisGood 8mo ago
    Why do you assume they’ll figure it out when they pretty consistently mess things up?
    - dripdry45 8mo ago
      That’s my take. Without any competition, they languish and do nothing, ruining any promising ideas.
    - weatherlite 8mo ago
      How do they consistently mess things up ? Current market cap 3.7T, only Apple and Nvidia are bigger. Youtube is a huge success, Search is still growing at 10%-15% which is crazy, cloud growing at 35%ish, TPUs enable them to be independent from NVidia etc. Gemini market share went up from 5%-6% early 2025 to 21% early 2026. I personally bet Gemini market share will keep growing. They are executing well on all verticals imo, not messing up.
      - starfallg 8mo ago
        Exactly. You might not like what Google does, but you can't deny it's a massive commercial success. Just because their approach to creating and delivering apps might not be to your liking, you might actually be the niche.
dakolli 8mo ago
They all suck!!!
tempestn 8mo ago
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.
- pants2 8mo ago
  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.
  - tempestn 8mo ago
    I can only speak to my own experience, but for the past couple of months I've been duplicating prompts across both for high value tasks, and that has been my consistent finding.
  - maxwellcoffee 8mo ago
    Google actually has the BEST ratings in the AA-Omniscience Index: AA-Omniscience Index (higher is better) measures knowledge reliability and hallucination. It rewards correct answers, penalizes hallucinations, and has no penalty for refusing to answer. Gemini 3.1 is the top spot, followed by 3.0 and then opus 4.6 max
    - holbrad 8mo ago
      This isn't actually correct. Gemini 3.0 gets a very high score because it's very often correct, but it does not have a low hallucination rate. https://artificialanalysis.ai/#aa-omniscience-hallucination-rate https://artificialanalysis.ai/#aa-omniscience-hallucination-... It looks like 3.1 is a big improvement in this regard, it hallucinates a lot less.
      - tempestn 8mo ago
        Yes and no. The hallucination rate shown there is the percentage of time the model answers incorrectly when it should have instead admitted to not knowing the answer. Most models score very poorly on this, with a few exceptions, because they nearly always try to answer. It's true that 3.0 is no better than others on this. By given that it does know the correct answers much more often than eg. GPT 5.2, it does in fact give hallucinated answers much less often. In short, its hallucination rate as a percentage of unknown answers is no better than most models, but its hallucination rate as a percentage of total answers in indeed better.
da_chicken 8mo ago
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.

bluegatty 8mo ago

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 8mo ago
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.
- bluegatty 8mo ago
  OAI Pro is not a 'research' tool in that sense, and it's definitely different than the 'deep research' options avail on most platforms, as I indicated. It's a different kind of solution altogether. I suggest trying it.
  - luipugs 8mo ago
    It's a different kind of solution :)
jswny 8mo ago
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.
- bluegatty 8mo ago
  It's a different model and designed to 'think very hard' about issues. It's basically a 'very extended thinking mixed with research' type of solution. While the 'research' solutions tend to go very wide and come back with a 'paper' the Pro model seems to do an exhaustive amount of thinking combined with research, and tries to integrate findings. I think it goes down a lot of rabbit holes. I find it's by far the best way to find solutions to hard problems, but it typically does require a 'hard problem' in order to shine. And it takes an enormous amount of time. Ito could be essentially a form of 'saturating the problem with tokens'. It's OAI's most expensive model by far. A prompt usually costs me $1-3 if paying per token.
- szundi 8mo ago
  [dead]

jacquesm 8mo ago

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.

frogperson 8mo ago

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 8mo ago
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.
- LPisGood 8mo ago
  Why do you assume they’ll figure it out when they pretty consistently mess things up?
  - dripdry45 8mo ago
    That’s my take. Without any competition, they languish and do nothing, ruining any promising ideas.
  - weatherlite 8mo ago
    How do they consistently mess things up ? Current market cap 3.7T, only Apple and Nvidia are bigger. Youtube is a huge success, Search is still growing at 10%-15% which is crazy, cloud growing at 35%ish, TPUs enable them to be independent from NVidia etc. Gemini market share went up from 5%-6% early 2025 to 21% early 2026. I personally bet Gemini market share will keep growing. They are executing well on all verticals imo, not messing up.
    - starfallg 8mo ago
      Exactly. You might not like what Google does, but you can't deny it's a massive commercial success. Just because their approach to creating and delivering apps might not be to your liking, you might actually be the niche.

dakolli 8mo ago

They all suck!!!

tempestn 8mo ago

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.

pants2 8mo ago
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.
- tempestn 8mo ago
  I can only speak to my own experience, but for the past couple of months I've been duplicating prompts across both for high value tasks, and that has been my consistent finding.
- maxwellcoffee 8mo ago
  Google actually has the BEST ratings in the AA-Omniscience Index: AA-Omniscience Index (higher is better) measures knowledge reliability and hallucination. It rewards correct answers, penalizes hallucinations, and has no penalty for refusing to answer. Gemini 3.1 is the top spot, followed by 3.0 and then opus 4.6 max
  - holbrad 8mo ago
    This isn't actually correct. Gemini 3.0 gets a very high score because it's very often correct, but it does not have a low hallucination rate. https://artificialanalysis.ai/#aa-omniscience-hallucination-rate https://artificialanalysis.ai/#aa-omniscience-hallucination-... It looks like 3.1 is a big improvement in this regard, it hallucinates a lot less.
    - tempestn 8mo ago
      Yes and no. The hallucination rate shown there is the percentage of time the model answers incorrectly when it should have instead admitted to not knowing the answer. Most models score very poorly on this, with a few exceptions, because they nearly always try to answer. It's true that 3.0 is no better than others on this. By given that it does know the correct answers much more often than eg. GPT 5.2, it does in fact give hallucinated answers much less often. In short, its hallucination rate as a percentage of unknown answers is no better than most models, but its hallucination rate as a percentage of total answers in indeed better.

da_chicken 8mo ago

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.