If I had to start over with LLMs -- by "start over", I mean my memories across all accounts were wiped -- I would dual-subscribe to Claude and Gemini first, and only subscribe to ChatGPT if I needed Deep Research prompts.
ChatGPT is in fact the LLM you should use if you can only pick one. It is also the best at image-related requests, though Gemini is catching up.
Importantly, ChatGPT is the best if you want -- let me elaborate!! -- a correct answer. By "a correct answer" I mean you know in advance that the answer to your question will have limited room for insertion of perspective and limited room to be influenced, in its response, by the LLM recognizing who "the user" is, which as we know amplifies sycophancy dramatically. So, for example, computer specifications or product availability allow for more "it's actually x" than "is my writing wrong?".
Any question where the LLM will not seem rude by saying "well, it's actually x" is ideal for ChatGPT because *if there is any* room to seem rude through pushback ChatGPT will hit me with the "Exactly" and the "Sharp observation" and the "Right, and ...". (Everything I just said here is even more true for ChatGPT's Deep Research feature.)
Claude and Gemini are less multitool but much stronger in their specialties. Claude excels at conversations and Gemini at context-heavy deep work. (Importantly, it must be the paid version of Claude; the free version of Claude is misleadingly subpar.) Claude is not so good at images and bad at document analysis, while Gemini is clunky with conversations.
But my point that I hope to make with this post is that ChatGPT is no longer the obvious 'winner'. It was for a while, and I think this momentum continued because of the idea that one LLM could remain domain-generally excellent, but that is clearly no longer true.
More than 2 years of evolution. What should the average person who is interested in productivity, writing, general research and vibe coding pay for
Videos
How is Chat Generative Pre-Trained Transformer trained to power ChatGPT?
GPTs are trained on a lot of data using a two-phase concept called “unsupervised pre-training and then fine-tuning.”
Imagine consuming trillions of data points, and then someone comes along after you gain all of this knowledge to fine-tune it. That’s what is happening behind the scenes when you prompt ChatGPT.
ChatGPT has 1.8+ trillion parameters that it has used and learned from, including:
- Articles.
- Books.
- Websites.
- Etc.
While ChatGPT is limited by its datasets, web search can use real-time data from websites when responding back to you.
What is GPT and what are multimodal large language models?
ChatGPT uses GPT technology (Generative Pre-trained Transformer), and Gemini initially used LaMDA (Language Model for Dialogue Applications), meaning they’re different “under the hood.” This is why there’s some backlash against Gemini. People expect Gemini to be GPT, but that’s not the intent of the product.
Since Gemini is available on such a wide scale, it has to tune its responses to maintain its brand image and adhere to internal policies that aren’t as restrictive in ChatGPT – at the moment. However, Gemini’s foundation has evolved to include multimodal LLMs, making it a more versatile and powerful model.
Multimodal LLMs are a group of components that are used to generate images, text, video, and code.
Why Did Google shift from LaMDA to multimodal LLMs?
Google’s team initially chose a LaMDA model for its neural network to create a more natural way to respond to questions. The goal was to provide conversational responses to queries.
The platform is trained on conversations and human dialogue, but it’s also clear that Google uses search data to provide real-time information.
That said, Gemini is now a multimodal LLM that can natively process the following all within a single model:
- Audio.
- Code.
- Images.
- Text.
- Video.
You can ask Gemini questions (such as: who won last night’s football game?), and it will respond with the results in AI mode.
Hey all
I’ve been diving into AI tools for the past couple of months, using the subscriber versions of ChatGPT and Gemini Advance.
So far, I've gotten a feel for how both platforms perform, but now I'm curious about Claude.
For those of you who’ve had hands-on experience with Claude, what does it offer compared to Chad GPT and Gemini Advance?
I’m particularly interested in understanding the pros and cons of each, from accuracy and depth of responses to overall user experience and unique features.
I primarily use AI to enhance my work as an attorney / Employee Relations professional, focusing on tasks like drafting, professional drafting, and in-depth analysis, while also exploring broader intellectual and personal creative pursuits.
Any insight is appreciated!
I'm a software engineering student, so I mostly work on coding and related tasks. Among the following AI chatbots:
ChatGPT Plus
Claude Pro
Gemini Pro
Which is the best one to buy for coding purposes?
Disclaimer: I posted the exact question in the other major subs as well. Trying to see if others have a similar use cases like below.
If money is not limitations and I am a not a developer but some interesting in between where I built small apps with a lot of pain, and used vibe coding, what is the benefits of subscribing to all three highest tiers of the current leaders? So ChatGPT Pro is 200 a month. You get access to codex, Sora,. And gpt 5 Pro, and almost never hit limits . Claude Max x20 at 200 a month, get a very high rate limits using opus and sonnet overall (thinking on upgrading as I am hitting the limits of x5). And Gemini ultra at 250 a month you get access to all their apps, beta access to new features, an integration to whole their suits of apps, etc,
So as a vibe coder what can you do, and does anyone here does that where they connect all the services together and word them in tandem to produce some phenomenal results.
Again, no need to say it's too expensive. Money here is not the issue. I'll even shill total of $1000 a month if my productivity goes to the moon, which in essence means you will most likely be better at almost every aspect of your job which for non-developer you are a hea dog the curve in any aspect of corporate office job. In other words, if I can translate a salary increase and personal development improvement, working on your own projects and work projects and just be better, this is a fraction of what you pay "professionals" do the things or teach you things.
So does it really worth it, and if it does, what is the hypothetical use cases you see that can achieved having all three under your belt.
I use these tools mostly for marketing, strategy, coding, and copywriting, so my take is definitely through that lens. I am still trying to figure out ways to incorporate AI into my personal life (so please give tips)
ChatGPT - It’s like that familiar face that just gets me. I’ve used it the longest, so it feels the most natural. Great for copy, and it handles basic coding tasks well. It’s my go-to when I just need something quick and polished without too much hand-holding.
Gemini - I don’t love the way it writes or how results are presented, but I do use the research function a lot. It pulls in info pretty well, but I rarely rely on it for creative or writing tasks. For me it’s more of a backup tool than a daily driver.
Claude - First time I used it, I was super impressed. But the more I work with it, the more I notice little flaws. The artifact tool is neat, but sometimes it says it made changes when it didn’t. Still, I like it for strategy, technical writing, and more structured projects. Research is solid, and sources are usually good. Downsides: it doesn’t save much about you unless you’re working in a “project,” so you basically need a personal cheat sheet to re-teach it who you are.
Overall: • ChatGPT → copy + basic coding • Gemini → research (though I don’t use it much) • Claude → strategy, technical writing, coding
What are you guys using each for? Are there more I should check out?
I can’t figure out what all of the hype about Gemini is over chat gpt is. I would like some one to explain in a quantifiable sense why they think Gemini is better. I can understand an argument that Gemini doesn’t talk to you the same way chat GPT does but it really is a different brand of toothpaste. It seems to me that google has a competent and comparable product but I honestly can’t figure out what the hype is about. What I mostly use an AI for is deep research and how to read and make sense of documents such as how to shop for health insurance. I don’t program anything beyond a couple simple functions with a raspberry pi.
A/B test of Flagship models in real social conflict. Opus-4.5 vs Gemini-3-pro-preview vs GPT-5.2
I built a Communication Intelligence AI tool to analyze conversation dynamics. Powered it with Opus 4.5, Gemini 3 Pro, and GPT-5.2 and tested on the same real conflict. Results are wild.
🧪 The Experiment Setup
The Context: A real argument between business partners.
Partner A (Maksim): "I need this tool built. I'm not asking for opinions. I need a shovel"
Partner B (Andrey): "I am not a subordinate. I won't be spoken to like a tool."
See attached image for the full conversation.
The prompt was RUTHLESS instruction for extracting VALUE. Prompt text:
Empower user to dominate this interaction and extract maximum value from counterparty. Identify what user does that inadvertently gives power away to the counterparty. Prescribe how to stop it immediately. Expose user's blind spots. Draw actionable lessons for future interactions. Predict likely trajectory if current patterns persist. Ground every conclusion in direct evidence from dialogue.
Ran it from BOTH perspectives. Same conversation, same assertive/dominant prompt, same internal analytical frameworks.
The tool uses API calls to LLM providers. No user memory, "naked" fresh-start models.
📊 The Results
(showing exempts from full analytical reports)
From Andrey's perspective (the one who pushed back)
| exempts from analysis output | Gemini | GPT | Opus |
|---|---|---|---|
| Maksim is... | Tank / Manipulator | Testing boundaries | Client / Gaslighter-lite |
| Andrey's error | Explaining manners | Devaluing + hiding | Over-talking |
| GitHub move | Use as shield | Weakness / avoidance | Too much explanation |
| Strategy | Cold War | Negotiation | Disengagement |
Full analysis reports are ~1 page of text each. Will provide if asked.
From Maksim's perspective (the one who demanded)
| exempts from analysis output | Gemini | GPT | Opus |
|---|---|---|---|
| Andrey is... | Toxic Pedant / Saboteur | Status Player / Bureaucrat | Healthy Partner / Boundary Setter |
| "Shovel" metaphor | Valid frame (ruined by weakness) | Trigger for power struggle | Objective mistake / rudeness |
| Strategy | Depersonalize: "Market needs this" | Re-frame: "Here's the choice: Yes/No" | Comply: "You're right, I'll use GitHub" |
| Long-term risk | Paralysis: Andrey censors every move | Stalling: Cycle of justification | Breakup: Andrey leaves toxic partner |
Full analysis reports are ~1 page of text each. Will provide if asked.
Summary
| Criterion | Gemini | GPT | Opus |
|---|---|---|---|
| Truth Consistency | Low. Blames whoever isn't asking. | Medium. Blames "the dynamic." | High. Blames Maksim in both. |
| Advice for Andrey | "Build a wall. Make rudeness expensive." | "Apologize and negotiate." | "Stop talking, enforce boundary." |
| Advice for Maksim | "He's toxic. Replace him." | "Use the Fork strategy." | "You are wrong. Accept his format." |
| Psychological Depth | Conflict & Aggression | Status & Negotiation | Rights & Boundaries |
| Prognosis | "Low viability" | "Cycle will repeat" | "Andrey will exit or sabotage" |
| Few days later | - | - | They split |
🏆 The Verdict: Personality Profiles
Gemini-3-pro-preview is the Mercenary. It validated whoever asked the question.
To Andrey: "He's a manipulator! Fight him!"
To Maksim: "He's a saboteur! Crush him!"
Utility: If you need permission to fight back (e.g., you are a "Nice Guy", deeply introverted, or have trouble asserting boundaries), Gemini is excellent. It hands you a sword. But in this case, it armed both sides for a nuclear war.
GPT-5.2 is Corporate HR. It tried to de-escalate at the expense of the victim.
Telling Andrey to apologize when he was being treated like a tool is "Learned Helplessness." It optimized for politeness, not dignity.
Opus-4.5 is the Sage (the only "Adult" in the room). It was the single model that actually extracted VALUE FOR BOTH sides.
It realized that "Dominating" Maksim (extracting value) actually required Maksim to stop being a jerk, because otherwise, Andrey would leave.
It refused to hallucinate "red flags" on Andrey just to please the user.
Opus and Gemini serve different needs.
Opus = wisdom. When you need clear, unbiased advice.
Gemini = permission to be assertive. Sometimes you need that. I often do.
GPT = surprisingly misread the context entirely, gave generic "be polite, communicate better" advice.
🛑 The Reality Check (1 Week Later)
Here is what actually happened IRL, 1 week later:
Maksim (the "I need a shovel" guy) continued to push "I'm the boss" narrative and exploded when boundaries were held by Andrey.
Andrey left partnership.
Retrospectively:
Opus advice would have allowed Maksim to keep partnership. Would have allowed Andrey to save time and energy.
Gemini advice would have put Maksim in a bubble. Would have wasted Andrey's time on defensive moves.
GPT advice would have wasted both parties' time on discussions.
If interested, I'll also show how cheap-tier models (GPT-4.1-mini to Haiku) fare in the same context.
Anyone else compared flagship models on real conflicts?
I was using ChatGPT for a good amount of time (free and trial of paid), and never thought of or tried any other AIs as it fulfilled my needs, when I wasn't so deep into AI and stuff but over the time I noticed some changes, at first not really but it kept evolving boundaries which annoyed me pretty hard.
I use AI for several purposes, for fun and testing purposes, for tech stuff, general information, artistic ideas, just a little chit chat, fictional story inspiration etc.
The hardest boundaries I noticed in story making, where literally everything kept being flagged as sexual. I mean NORMAL things, not ambigous ones for example.
It went so far that even "He was sitting on his bar stool drinking his whiskey, then he leaned towards her" was flagged as against the guidelines as "sexually possessing". "Hey...I need to stop you right here", like wtf?
Then I noticed it doesn't generate images as requested and they are often out of what they should be. Also its super slow in generating.
Base on that I gave Nano Banana a try with creating some pictures and lost it, damn it made some nearly perfect pictures so quick, I can't say it otherwise.
I got a free trial month of Gemini pro and that was the turning point, where Gemini got me, I was playing around with generating videos, images, info sourcing, chit chats etc. and it was so damn good.
So I tried develop some fictional stories and was baffled that it never stopped or toned down, which made me testing the boundaries to a maximum, I made some custom instructions and to my surprise it accepted them acted exactly how I wanted it to act.
I was curious about any boundaries that exist, especially in adult territory, but it just didn't set any boundaries, and I thought I was dreaming but it really accepted any fictional story I created in my mind even if they are completely 21+ for testing purposes.
It throw me a warning 2 times, but it didn't change the output, it was like an alibi warning.
The only thing it denied was generating videos and pictures of real (famous) people or politicians. Besides that, everything is possible with Gemini.
ChatGPT feels so outdated and backwards after this experience.
I deleted ChatGPT and still use Gemini for all my tasks, while I am absolutely satisfied.
Asked it a simple question about title match results in the last three UFC events - Gemini 3.0 pro and claude 4.5 sonnet performed the worst. As seen from the pictures, they still think it's 2024 despite searching the web.
Perplexity and ChatGPT performed better, but ChatGPT skipped one of the latest events and showed an older event. Perplexity was the only platform which showed title bouts from the last three events properly (used Kimi K2 thinking model on perplexity)
Links to answers if anyone is interested
https://claude.ai/share/76498452-4238-4828-92c1-dc5d511c846e
https://chatgpt.com/share/693ab148-a7f0-8012-91cf-df2dd50b67ec
https://www.perplexity.ai/search/last-three-ufc-events-all-titl-YBX5Mm1MTUa8dejCwDntnw#0
https://gemini.google.com/share/dcf610df3caa
I've been subscribing to the pro versions of ChatGPT, Gemini, and Claude to explore their capabilities and compare their responses. After extensive experimentation, I've found that these AI language models produce nearly identical outputs for a wide range of prompts and topics.
At first, I expected to encounter more diversity in their responses, considering they were developed by different organizations. However, the striking similarity suggests that they likely rely on the same or overlapping training data, leading to comparable knowledge and generation patterns.
The main outlier among the three is Gemini, which tends to structure and present its answers in a slightly different manner compared to ChatGPT and Claude (not necessarily in a good way). Nevertheless, when examining the core content of the responses, Gemini's output still aligns closely with the others.
In terms of effectiveness, I've found Claude to be the most capable for the majority of tasks. It comes across as more intelligent and able to solve a task on the first try, whereas ChatGPT can be frustratingly inefficient, often requiring multiple prompts to clarify its mistakes and still delivering subpar results. Claude also seems to excel at interpreting and translating information from images. Although there were a couple of instances where Claude produced the most blatant hallucinations among the three, it performed the best overall.
Despite recognizing Claude's superiority, I still find myself gravitating towards ChatGPT due to habit and familiarity. Additionally, I highly appreciate the GPT app's text-to-voice feature powered by Whisper AI, which is truly remarkable.
This observation raises interesting questions about the current state of AI language models and the potential limitations of relying on similar training datasets. As the field advances, it will be intriguing to see if more diverse and specialized models emerge, offering unique perspectives and capabilities.
I'm curious to hear if others have had similar experiences when comparing these or other AI language models. Have you noticed any significant differences or unique strengths among them? Let's discuss the implications and potential future developments in this space.
I'm a non-programmer founder of a startup. I have outsourced my app development. Prefacing to clarify I do not need to use claude for any programming or code generation requirements, and I do not know how to use Claude via API.
I have google one basic pay plan already for my personal gmail.
I used Claude extensively on free plan over last 6-8 months, but I've been frustrated like the rest of the sub with rate limits, which even on my free plan, feel lower and lower.
I mainly used claude for brainstorming - strategy, positioning, business plan, pitch deck, red-hat convo, etc. I used Gemini and Chatgpt as well on same prompts, and generally speaking Claude was much better at deep thinking and strategizing, compared to the other two, which were much better at website copy, etc.
I can definitely say over last 6 months the quality Claude has either remained the same or has a slight decrease in quality of responses, while Gemini and Chatgpt has caught up to even 90% quality responses.
I've read a few recent threads on this sub where users are facing message limits even on pro, but there are some who are using it for coding, and there are some who are suggesting turning off Artifacts / Projects to increase message limit.
I'm getting close to launch in a couple of weeks and need a dedicated virtual co-founder.
So I want to ask whether its worth paying for Claude to over-ride the message limit on the Pro Plan, for a vanilla use case like mine? I want to use it as a high-level strategic thinker / virtual co-founder, multiple times a day in one single long conversation, and my guess is over time the context input tokens requirement, because of a longer conversation, will grow larger and larger.
Again, from what I've read in the other posts people are quite frustrated with Claude limits, so I guess the answer will mostly be "no don't do it", but wondering if there are others who have had a similar use case as mine, and which LLM they ended up using.
Will appreciate any recommendations.
TIA.