As soon as Gemini 2.5 Pro Experimental was made free, the whole YouTube and Reddit went abuzz with how good it was. I too started using it once Google launched a free version.
Just within a week, I use it for making blog outlines from sources I give. For getting the sources, I use Google NotebookLM’s ‘Discover Sources’ feature which is so much better than usual Google search. This has replaced ChatGPT and Claude for my current workflows.
The artificial intelligence engineering landscape is in constant, rapid flux. Just when we thought we understood the pecking order, a new model or feature emerges, shaking up the status quo.
Then, I came across this post on Reddit about how ChatGPT 4.5 is a joke:
For a long time, OpenAI’s ChatGPT reigned supreme, capturing the public imagination and becoming synonymous with generative AI. But the ground is shifting.
Google’s Gemini, particularly its more advanced iterations like Gemini 2.5 Pro, is not just knocking on the door. It is really good. People churning our SaaS apps or browser games in minutes is crazy.
But I have experienced Gemini 2.5 Pro is not great at maintaining context of past conversations within a chat to improve responses.
For example, if I ask it to produce a blog post outline, it gets confused when asked it to include a certain topic later on. It changed the whole blog post to include the topic instead of making a single section.
I wondered if I was the only one facing these hiccups.
A week after making Gemini 2.5 Pro available for free, I noticed a few social media posts on how people switched back to ChatGPT.
This made me research more on how does Gemini 2.5 Pro perform compared to ChatGPT, and if it is worthy of a switch.
In this blog post, I will cover:
- What’s driving this shift in perception and, for some, usage to Gemini 2.5 Pro from ChatGPT?
- Why are some users, particularly those pushing the boundaries of AI capabilities, finding Gemini increasingly compelling?
- Why does ChatGPT still hold such a strong grip on the market?
- Resources – reviews and opinion posts I considered to compile here on this blog.
Advantages of ChatGPT vs Gemini 2.5 Pro – the OpenAI ecosystem ‘moat’ since 2023 launch
It’s impossible to discuss the current AI landscape without acknowledging ChatGPT’s monumental impact. It made the abstract concept of large language models into something tangible. This transformation created an accessible tool that fundamentally changed how people interact with AI.
Since its launch in 2023, ChatGPT’s strengths as of today are immediately obvious:
- Conversational Fluency: An intuitive ability to understand and generate human-like text made it incredibly easy to use.
- Versatility: From drafting emails and debugging code to writing poetry and explaining quantum physics, its range was unprecedented.
- Ecosystem Maturity: The development of the GPT Store allowed users to create and share custom AI agents (GPTs) for specialized tasks. This ability added immense value. It also fostered a dedicated community of GPT creators.
Today, whenever a new model releases, it is directly compared to ChatGPT.
We can tailor ChatGPT for specific workflows to create specialized or vertical AI agents. One can create custom assistants for coding, data analysis, academic research, creative writing, and countless other niches. This ecosystem represents a significant moat – a reason for users invested in specific GPTs or workflows to stay put.
All of this, along with the first mover advantage, makes switching to newer models difficult, even if they are better.
Limitations of ChatGPT compared with Gemini 2.5 Pro
However, alongside the praise, a narrative of discontent has been simmering, often bubbling up in online forums:
Perceived decline in quality (‘Lobotomization)
A frequent complaint over the past year or so is that newer iterations of GPT-4 (including GPT-4o) feel “dumber”.
They feel less creative or more prone to providing generic, uninspired answers compared to earlier versions. Whether this is due to safety tuning, optimization choices, or other factors, the perception persists among some power users.
Increased refusals and ‘Laziness’
There are many instances where ChatGPT refuses to perform tasks it previously handled. For this, it cites safety concerns or policy restrictions, sometimes seemingly arbitrarily. There are also complaints about the model giving up mid-task or providing incomplete code or answers.
Reasoning and complexity limits
ChatGPT is capable. However, users pushing complex logical problems may find limitations. Complex multi-step reasoning often hits a wall sooner than expected. Intricate coding challenges can contribute to these limitations.
Anything requiring logical problem assessment or deep analysis of very large datasets sometimes find ChatGPT reaching its limits.
Context window limitations (Historically):
ChatGPT is improved with models like GPT-4o. However, it historically had limitations in processing very long documents. It also struggled with maintaining context over extended conversations. Some competitors are now offering better performance in these areas.
Despite these points, ChatGPT’s dominance is far from over.
Its user base is enormous. Interface familiarity breeds efficiency, and many users have integrated it deeply into their workflows.
For countless everyday applications, it remains a powerful and reliable tool. It is useful for quick summaries, brainstorming, content generation, and basic coding help. The value provided by its mature ecosystem of specialized GPTs is a significant factor keeping users engaged and loyal.
For many, it simply works well enough. For casual users or those whose needs aren’t pushing the absolute limits, the need to switch is not there.
Advantages of Gemini 2.5 Pro vs ChatGPT – with the ‘moat’ of Google ecosystem
Google’s entry and rapid iteration in the generative AI space with Gemini have been formidable.
While early versions faced mixed reviews, the launch of models like Gemini 1.0 Ultra and, more significantly, Gemini 2.5 Pro (often the focus of recent positive comparisons) marked a turning point. User testimonials, particularly from those using the advanced, paid tiers, highlight several key areas where Gemini is perceived to excel:
The colossal context window (Gemini 1.5 Pro)
This is perhaps Gemini’s most significant differentiator at present. Gemini 1.5 Pro has a context window capable of handling up to 1 million tokens. This is equivalent to hours of video, hundreds of thousands of lines of code, or massive documents!
This large context window unlocks new possibilities:
Users have successfully feed an entire codebase for analysis and debugging.
You can feed long research papers for summarization and critique.
You can share extensive transcripts for thematic analysis.
You can even use video content for generating description and Q&A.
These capabilities are often cited for the ones who switched from ChatGPT to Gemini 2.5 Pro. These tasks that were earlier impractical or impossible with ChatGPT’s historically smaller context limits. One had to struggle or need cumbersome workarounds.
Advanced reasoning and logic
Many users, especially those dealing with complex technical, scientific, or logical problems, report that Gemini exhibits superior reasoning abilities. It seems better equipped to follow intricate instructions, perform multi-step logical deductions, and solve challenging puzzles or coding problems.
For example, in this video, both models are fed the same complex prompt. One can find Gemini’s response more accurate, insightful, or logically sound.
Some users describe it as feeling more like a “thinking partner” for difficult tasks.
Coding prowess
While ChatGPT (especially GPT-4) has been a valuable coding assistant, many developers on Reddit claim Gemini (particularly 1.5 Pro) offers more robust and accurate coding support.
This includes generating cleaner code with better explanations. Debugging complex issues is more effective, aided by the large context window for analyzing entire projects. Additionally, it translates code between languages with higher fidelity.
Handling nuance and instruction following:
Some users perceive Gemini as excelling at understanding subtle nuances in prompts. It adheres strictly to complex, multi-part instructions without deviation or hallucination. This is compared to recent ChatGPT experiences.
Integration potential (Google Ecosystem)
Gemini Extensions are still evolving. Their potential for deep integration with Google Workspace (Docs, Sheets, Gmail, Drive) is a significant draw. This is especially true for users heavily invested in Google’s ecosystem. The ability to seamlessly call upon Gemini within these applications promises significant workflow efficiencies. This is also a key reason why I have shifted to Gemini.
Multimodal capabilities
Gemini models are inherently multimodal. They are designed from the ground up to understand and reason across text, images, audio, and video. This design offers versatile input and output possibilities.
ChatGPT vs Gemini 2.5 Pro – feature comparison
Let’s compare ChatGPT and Gemini 2.5 Pro features and advantages based on below aspects:
| Feature/Parameter | ChatGPT (GPT-4 / GPT-4o based) | Advanced Gemini (e.g., Gemini 1.5 Pro) | Notes |
| Context Window | Improved (e.g., 128k tokens for GPT-4 Turbo/4o), capable for many tasks, but generally smaller than top Gemini models. | Industry-leading (up to 1M tokens+), excels at processing and analyzing vast amounts of information (long documents, codebases, video). | This is a major differentiator, enabling use cases difficult or impossible for models with smaller context windows. |
| Reasoning & Logic | Strong general reasoning capabilities, handles many complex tasks well. Some users report limitations on highly intricate or multi-step logical problems. | Often perceived by users as superior for complex, multi-step reasoning, logical deduction, and problem-solving, especially with large amounts of data. | This is often cited as a key reason users prefer Gemini for demanding analytical or technical tasks. |
| Coding Assistance | Very capable and widely used for code generation, explanation, and debugging. Works well for many standard coding tasks. | Highly praised, particularly for complex code generation, debugging within large codebases (aided by large context), and accurate explanations. | Gemini’s ability to analyze entire repositories is seen as a significant advantage by many developers. |
| Creative Writing Style | Often preferred for its engaging and versatile creative writing style. Can generate various tones and formats effectively. | Capable creatively, but sometimes described by users as potentially more verbose, formal, or slightly less “natural” sounding compared to ChatGPT. | This is highly subjective and depends heavily on user preference and the specific creative task. |
| Ecosystem | Mature and extensive ecosystem via the GPT Store (custom GPTs) and formerly Plugins, offering many specialized tools. | The ecosystem based on Extensions is developing and growing. It is integrating with Google products. Yet, it presently lacks the sheer volume of ChatGPT’s GPT Store. | ChatGPT now holds a significant advantage in the breadth and maturity of its third-party/custom agent ecosystem. |
| Multimodality | Strong multimodal capabilities (GPT-4o handles text, audio, image input/output seamlessly). | Designed natively for multimodality (text, image, audio, video), allowing deep integration and reasoning across different data types. | Both platforms are highly capable; Gemini’s native design might offer advantages in complex cross-modal reasoning. |
| Speed | Generally fast response times, with GPT-4o showing significant speed improvements. | Performance is generally fast but can vary depending on the complexity of the query and context size. | Speed is often comparable, but specific task performance can differ. User perception varies. |
| Accuracy / Factuality | Generally reliable for factual information but remains susceptible to “hallucinations” (generating incorrect information confidently). | Generally reliable but also susceptible to hallucinations, especially on obscure topics or complex inferences. Requires user verification. | This is an ongoing challenge for all large language models; critical information should always be verified. |
| User Interface (UI) | Clean, intuitive, and familiar interface, widely considered very user-friendly. Offers web and mobile apps. | Clean interface, well-integrated with the Google ecosystem (especially for Gemini Advanced users). Offers web and mobile apps. | Both offer polished UIs; preference is largely subjective and may depend on familiarity with Google products. |
| Instruction Following | Generally follows instructions well, but users sometimes report issues with adherence to very complex, multi-part, or nuanced prompts. | Often praised by users for its precision in adhering strictly to complex, detailed, and nuanced instructions. | Gemini is frequently perceived as more reliable for tasks requiring meticulous execution of specific constraints. |
| Maturity / User Base | More established platform with a larger user base and longer period of public refinement and feedback. | Newer platform relative to ChatGPT, rapidly evolving, with a growing but currently smaller user base providing feedback. | ChatGPT has benefited from more extensive real-world testing and iteration based on user interactions. |
So, should you switch to Gemini 2.5 Pro from ChatGPT?
Here are, as per my experience and research, why one can switch from ChatGPT to Gemini 2.5 Pro. Note that the decision boils down to individual needs and priorities
Reasons to consider switching to (or adding) Gemini:
- Need for large context analysis: If your work involves analyzing long documents, entire codebases, extensive transcripts, or large datasets, Gemini 2.5 Pro’s context window is a compelling, perhaps necessary, advantage.
- Focus on complex reasoning/problem solving: For tasks requiring deep logical deduction, intricate planning, or solving complex technical challenges, rely on Gemini. Its perceived strengths in reasoning offers better results.
- Advanced coding requirements: Developers working on large, complex projects may find Gemini’s coding assistance very powerful. It is aided by its context capabilities.
- Frustration with ChatGPT limits: If you consistently face refusals, perceived “laziness,” or find ChatGPT hitting a wall on your specific complex tasks, exploring Gemini is a logical next step.
- Leveraging multimodality: If your workflow involves integrating analysis across text, images, audio, or video, Gemini’s native capabilities are a distinct advantage.
Reasons to stick with ChatGPT (or use it primarily):
- Reliance on the GPT ecosystem: If your workflow depends heavily on specific custom GPTs available only in the GPT Store, staying makes sense.
- General purpose use: For everyday tasks like drafting emails, writing articles, and brainstorming, ChatGPT excels. It often performs admirably and efficiently in general Q&A.
- Familiarity and efficiency: If you’re comfortable and productive with ChatGPT’s interface and interaction style, it may not be worth switching. A new platform might have a steep learning curve for your needs.
- Preference for interaction style: Some users simply prefer ChatGPT’s conversational style. Others find its outputs more aligned with their creative voice. Some users think it fits their professional voice better.
- Cost and feature bundling: Subscription tiers and included features, like integrations or storage, play a big role. One platform might offer better value for your specific budget. It depends on your specific requirements.
It’s not black and white: why the “best” AI is subjective
Despite the growing enthusiasm for Gemini, it’s crucial to keep perspective.
Use case is king
The “better” AI often depends entirely on the task. For creative writing prompts, some users still prefer ChatGPT’s style or find it more imaginative. For quick queries or general conversation, the differences might be negligible or favour ChatGPT’s often more concise style.
Keep Gemini’s quirks in mind
Gemini isn’t without its criticisms. Some users find it overly verbose compared to ChatGPT. Like all LLMs, it can still hallucinate or make errors, sometimes confidently. Its ecosystem of extensions is less mature than the GPT Store. User interface preferences also play a role.
Rapid evolution of AI models
The AI landscape moves incredibly fast. OpenAI is undoubtedly working on GPT-5. They are also making further improvements to GPT-4o. These efforts will potentially tackle current weaknesses. Additionally, they may introduce new capabilities that could leapfrog Gemini again. Google, similarly, will continue to iterate on Gemini. Today’s comparison is merely a snapshot in time.
Cost considerations
Both platforms offer free tiers with limitations and paid subscription tiers (ChatGPT Plus/Team/Enterprise, Gemini Advanced). The specific features included at each price point can influence a user’s decision, especially for those on a budget. Gemini Advanced often bundles access to the most capable models (like 2.5 Pro) and Google One storage, which might be attractive value for some.
Resources – reviews and opinion posts I referenced to compile this blog
Everything I have included on this blog has come from my own experience and these reviews and opinion posts. Your can refer to them below and also share your own experience with both AI models in the comments:
- The real reason why most ChatGPT users are not switching to Gemini despite 2.5 pro’s capabilities – Reddit Post
- My experience with Gemini 2.5 Pro and why I switched to OpenAI’s o1 / o3 models – Reddit Post
- ChatGPT 4.5 feels like a joke compared to Gemini 2.5 – Reddit Post
- Gemini 2.5 Pro vs. ChatGPT: Who Creates the Best Ghibli-Style Art? – Medium Article
- Gemini 2.5 Pro vs ChatGPT 4o: Real Test, Real Winner – YouTube
- I tested DeepSeek vs Gemini 2.5 with 9 prompts — here’s the winner – Tom’s Guide
- Gemini Pro 2.5 is a stunningly capable coding assistant – and a big threat to ChatGPT – ZDNet
AI engineering landscape shows how competition breeds innovation
The intense competition between Google’s Gemini and OpenAI’s ChatGPT is ultimately a win for users. It fuels rapid innovation, pushing both companies to enhance their models’ capabilities, improve performance, and add valuable features.
ChatGPT built the initial wave. It retains a massive, often satisfied user base thanks to its accessibility, familiarity, and ecosystem.
Gemini, particularly with models like 2.5 Pro, has mounted a powerful challenge. Its strengths in handling massive context, complex reasoning, and coding appeal to power users. Those pushing the limits of current AI technology notice these strengths. There is, thus, a noticeable shift in perception and usage patterns among this cohort.
There is no single “best” AI for everyone. The ideal choice depends on individual needs, specific use cases, budget, and even personal preference for interaction style.
The smartest approach for users, especially professionals relying heavily on AI, is to stay informed. They should experiment with both platforms by leveraging free tiers or trials. Professionals might even use both, tapping into each model’s strengths for different tasks.
The AI wars are far from over, and the next chapter promises even more exciting developments.
I will continue to cover about latest AI models and AI tools with a strong focus on practical use case. Subscribe to get the latest guides and tutorials:
Just when I was done with my research on ChatGPT vs Gemini 2.5 Pro models, I came across this adorable comment on a Reddit Post titled ‘ChatGPT feels like a joke’:
That’s right – we must test AI models, appreciate the latest improvements, and use as per our needs. No need to mock or brutally compare someone’s past work that lays foundation for future AI models.
What is your AI model stack these days and what’s the use case? – Let me know in the comments!
Learn more about AI models to understand their use case and science behind their optimizations in easy language:
- Vertical AI Agents Will Replace SaaS – Experts Warn On Future Of Workflow Automation
- Stanford’s S1 model – How Stanford built low-cost open source rival to OpenAI’s o1
- What is OpenAI o3-mini – technical features, performance benchmarks, and applications
- What is Alibaba’s Qwen2.5-Max – technical features, performance benchmarks, and applications
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