As your feed was flooding with Ghibli style images, it cemented ChatGPT’s image generation capabilities. Recently, it has stopped users from making these images after a backlash. More like, it allows creating Ghibli style images on its Pro version, thus monetizing the trend.
Google saw this trend – and now, has made its most intelligent model, Gemini 2.5 Pro, completely free.
And yes, it can too make the Ghibli style images!
Of course, there is more to this intelligent and benchmark shattering AI model than Ghibli images lol.
Gemini 2.5 Pro today is known for its exceptional reasoning capabilities. It is engineered to tackle complex problems ranging from advanced coding to nuanced decision-making. The model can analyze vast datasets. It processes diverse inputs and generates insightful responses. This puts it head-to-head with other leading models, including famous for stealing Studio Ghibli’s IP, OpenAI’s GPT-4.5.
In this blog post, I will cover now that Gemini 2.5 Pro is free, what can you do with this new free AI power!
- Features and benchmarks of Gemini 2.5 Pro
- Resources to implement Gemini 2.5 Pro best practices
What is Gemini 2.5 Pro? – making of the ‘most intelligence model’
Google’s Gemini series was initially unveiled in December 2023. It is the successor to LaMDA and PaLM 2. This began from the innovative collaboration between Google Brain and DeepMind. This partnership used cutting-edge advances ranging from the game-changing approach of AlphaGo to state-of-the-art transformer architectures. These innovations pushed the boundaries of what AI can achieve.
The early Gemini models laid the groundwork with impressive multimodal capabilities. They handled not just text but also images, audio, and video.
With Gemini 1.5, Google introduced a pivotal “step change.” This change dramatically increased the context window. It allowed models to process millions of tokens in a single pass. This evolution paved the way for even more sophisticated iterations like Gemini 2.0 Flash, which incorporated native tool use and real-time multimodal interactions.
The release of Gemini 2.5 Pro in March 2025 shows the current pinnacle of this evolution.
It is described as a “thinking model” that introduces advanced reasoning features. These allow the AI to pause, think, and generate responses in a structured chain-of-thought manner. These capabilities not only translate into improved performance on complex benchmarks— like scoring 18.8% on Humanity’s Last Exam and leading on math and science tasks. They also enhance practical applications like coding, document analysis, and multimodal processing.
With a groundbreaking 1 million token context window (and plans to expand to 2 million tokens), Gemini 2.5 Pro demonstrates how Google is redefining AI scalability and user-centric design.
This rapid evolution, from Gemini 1 to Gemini 2.5 Pro, highlights Google’s strategic focus on not only matching but surpassing competitors like GPT-4.5, by integrating human-like reasoning and robust multimodal inputs directly into the model’s core architecture.
The free roll-out of the experimental Gemini 2.5 Pro further underscores Google’s commitment to democratizing access to advanced AI tools while gathering real-world feedback for continual refinement.
What’s new with Gemini 2.5 Pro?
Gemini 2.5 Pro isn’t just another AI model. It signifies a significant leap ahead in how large language models reason. It processes complex tasks and handles vast amounts of data. That’s what makes it primarily different from its earlier model versions.
3 key advanced features of Gemini 2.5 Pro
Enhanced thinking capabilities:
Gemini 2.5 Pro is designed as a “thinking” model that pauses to reason through its response before outputting an answer. This enables it to deliver more accurate and context-aware responses, especially on complex queries.
Multimodal input handling:
Unlike traditional text-only models, it accepts not just text but also images, audio, and video. This multimodal ability allows users to integrate different data types into one conversation. It is exceptionally versatile for creative projects. It is useful for data analysis and interactive applications.
Native tool use and code execution:
The model can directly call functions, execute code, and generate structured outputs. This is particularly useful for developers looking to integrate AI into real-world applications without extensive additional programming.
Upgrading context window with Gemini 2.5 Pro
One key feature of Gemini 2.5 Pro is its ability to process up to 1 million tokens in a single prompt. There are plans to expand this ability further. This means it can understand and work with entire documents, long codebases, or extended conversations. It does this without losing track of earlier context. This is a game changer for tasks like document analysis or multi-turn dialogue scenarios.
With its long context window, users can see a clear trace of its reasoning process. This visibility helps in understanding how it arrives at an answer. This transparency not only boosts trust but also makes it easier to troubleshoot or refine outputs when necessary.
Benchmark performance of Gemini 2.5 Pro vs alternative AI models
That’s the official table released by Google on Gemini 2.5 Pro benchmarks:
Don’t worry, I will explain you what each of these benchmarks means in this section. Then, look for how Gemini 2.5 Pro performs for the benchmark of your interest in the above image:
- Humanity’s Last Exam: Evaluates complex reasoning and deep understanding across many subjects. If an AI model scores high for this benchmark, it is ideal for tasks requiring advanced thought processes. These tasks include research or expert Q&A.
- GPQA Diamond: Assesses science and factual question answering. If an AI model scores high for this benchmark, it is best for answering scientific or technical queries accurately.
- AIME 2024 & AIME 2025: Tests advanced mathematical problem-solving abilities. If an AI model scores high for this benchmark, it is excellent at solving complex math problems. It is also good at performing detailed calculations.
- LiveCodeBench: Determines quick one-shot code generation abilities. If an AI model scores high for this benchmark, it is perfect when you need a fast script. It is also ideal for simple code without much iteration.
- Aider Polyglot: Determines ability to edit and transform existing code. If an AI model scores high for this benchmark, then it is useful for refactoring code. It can also make precise improvements in multi-file projects.
- SWE-Bench Verified: Measures performance in resolving real-world software issues. This includes multi-step, agentic coding and planning tasks. If an AI model scores high for this benchmark, it is ideal for complex coding tasks. This is especially for tasks that need step-by-step planning and iterative fixes.
- SimpleQA: Focuses performance on answering short factual Q&A with a focus on accuracy. If an AI model scores high for this benchmark, it is ideal for straightforward, reliable answers to general knowledge questions.
- MMMU: Tests visual reasoning and understanding of images/mixed media. If an AI model scores high for this benchmark, it is perfect for projects needing image analysis. It is also ideal for projects combining different media types.
- MRCR: Long-context understanding over extended documents or conversations. If an AI model scores high for this benchmark, excellent for summarizing large documents or managing long, detailed dialogues.
- Global MMLU Lite: Checks for performance across multiple languages. If an AI model scores high for this benchmark, it is ideal for users needing strong multilingual support. It is also perfect for those requiring translation abilities.
Best AI model for each benchmark task:
One thing is clear: Gemini 2.5 Pro has demonstrated impressive results across multiple multiple benchmarks.
Yet, for some benchmarks, other AI models have performed better. I have shared a simpler table here with key benchmark comparison:
| Benchmark / Task | Best Model | Score | Recommended Use Cases |
|---|---|---|---|
| 1. Reasoning & Knowledge (Humanity’s Last Exam) | Gemini 2.5 Pro | 18.8% | Complex reasoning tasks, advanced Q&A, academic or expert-level topics. |
| 2. Science (GPQA Diamond) | Gemini 2.5 Pro | 84.0% | In-depth scientific queries, factual Q&A in STEM fields. |
| 3. Mathematics (AIME 2024 & AIME 2025) | Gemini 2.5 Pro | 92.0% (AIME 2024) | High-level math problem-solving, step-by-step calculations, math competitions. |
| 4. Single-Attempt Code Generation (LiveCodeBench) | OpenAI o3-mini | 74.1% | One-shot coding tasks or quick script generation (no multi-step iteration). |
| 5. Code Editing & Transformation (Aider Polyglot) | Gemini 2.5 Pro | 74.0% (whole-file) | Refactoring existing code, applying fixes, or reorganizing multi-file projects. |
| 6. Agentic Coding (SWE-bench Verified) | Claude 3.7 Sonnet | 70.3% | Large, multi-step coding tasks with agent-like planning or iterative solutions. |
| 7. Factual Q&A (SimpleQA) | OpenAI GPT-4.5 | 62.5% | General knowledge queries or short Q&A needing precise factual correctness. |
| 8. Visual Reasoning (MMMU) | Gemini 2.5 Pro | 81.7% | Understanding and analyzing images or multimodal input. |
| 9. Long-Context Tasks (MRCR) | Gemini 2.5 Pro | 94.5% (128k avg) | Handling or summarizing very large documents, extended conversations. |
| 10. Multilingual (Global MMLU Lite) | Gemini 2.5 Pro | 89.8% | Working across multiple languages or global content. |
When to use Gemini 2.5 Pro?
Gemini 2.5 Pro excels in reasoning, math, science, long-context tasks, visual understanding, and multilingual tasks.
The best use case for Gemini 2.5 Pro is when you want a single model that can handle complex or multimodal work (e.g., large documents, advanced math, or images) in many languages. I have also covered about combining Deep Research by Gemini with Google NotebookLM here: Learn NotebookLM For Beginners – 2025 Guide With FAQs Solved And Real Examples
Benefits of Gemini 2.5 Pro:
Enhanced coding capabilities:
Many developers praise Gemini 2.5 Pro for its advanced coding assistance. Users report that it handles large codebases effectively, provides incremental edits without unnecessary changes, and offers consistent performance.
A reviewer on Latenode observed that Gemini 2.5 Pro showed promising signs of understanding nuance in prompts. It was especially effective when defining output formats. It also excelled at specific tasks within a larger request.
Social media is filled with people building games, simulations, websites, SaaS, and much more! Explore the resources section towards the end – I have shared some interesting YouTube tutorials for this.
Extended context window:
The model’s ability to process extensive context is a significant advantage. Many early adopters have successfully used Gemini 2.5 Pro to resolve complex coding issues by using its large context window, allowing for comprehensive problem-solving.
Free accessibility
Gemini 2.5 Pro is available for free through platforms like Google AI Studio. That’s a lot of power for everyone now! Is Google going to launch something more insane than this AI model as ‘paid version’?!
Competitive performance:
In benchmarks and user comparisons, Gemini 2.5 Pro has demonstrated superior performance in coding tasks compared to other AI models.
Apart from this, I think Gemini will enter into the full Google ecosystem of products. Phones, Workspace, Educational apps, NotebookLM, and much more! That would be its biggest USP.
Limitations of Gemini 2.5 Pro:
Coding assistance limitations:
While Gemini 2.5 Pro excels in certain coding tasks, some users have reported challenges with larger codebases.
For example, one user on HackerNews noted that the model struggled with a 500-line code conversion. It encountered issues around line 300. These issues included hallucinations and incorrect code modifications.
Experimental release concerns:
As an experimental release, Gemini 2.5 Pro may present stability issues and unexpected behaviors. It is better to approach its outputs with caution and verify critical information independently. For example, I tried using it to build a SaaS website for tracking SEO keywords for fun. Despite a 1M token claim, it loses track of conversations after a few turns.
UX needs to improve for coding:
If its coding, then Gemini 2.5 Pro does not offer a dedicated user interface for the same. Platforms like Cursor, Lovable, or Replit would still be better options. There is no version tracking too and it can change whole code than making small changes. It also over-compresses logic into one-liners, making code difficult to read and maintain.
Using Gemini 2.5 Pro versus other AI models:
As per the latest benchmarks of AI models, here’s what I can conclude about their best use cases:
- For complex or specialized tasks (like advanced math, large-scale data analysis, or multimodal inputs), Gemini 2.5 Pro leads the pack.
- For coding, the choice depends on your workflow:
- One-shot generation → OpenAI o3-mini
- Iterative, agent-like coding → Claude 3.7 Sonnet
- Editing / large context → Gemini 2.5 Pro
- For straightforward factual Q&A, OpenAI GPT-4.5 has the highest accuracy.
Now, experience Gemini 2.5 Pro for free!
I found this interesting broad level video that covers some insane things you can do with Gemini 2.5 Pro! This includes building a pokedex, doing financial analysis, simulating bee colony, performing probability experiments, and much more:
Google surprised the market by making Gemini 2.5 Pro free to all users, shifting from its initial premium-only release. This improves its accessibility to students, startups, casual users and other daily professionals.
Note that free users face rate limits. They have fewer requests and token restrictions.
Premium subscribers enjoy benefits like longer context windows and higher throughput.
With free access, users can integrate Gemini 2.5 Pro into projects ranging from interactive simulations and code generation to large document analysis, accelerating practical AI adoption.
By offering this powerful model at no cost, Google is broadening its user base. It is also setting a competitive tone in the evolving AI landscape.
All set! – How to Get Started with Gemini 2.5 Pro
There are 2 ways to access Gemini 2.5 Pro:
Access Gemini 2.5 Pro via Google AI Studio:
Visit Google AI Studio and sign in with your Google account.
Gemini 2.5 Pro is available to all users in this environment. It provides a playground to test and interact with the model without upfront costs. This free access lets you experiment with its massive context window and enhanced reasoning capabilities before considering any advanced subscriptions
Access Gemini 2.5 Pro via the Gemini App:
For a more streamlined experience, select Gemini 2.5 Pro from the model dropdown in the Gemini app. Note that free users might experience certain rate limits. In contrast, Gemini Advanced subscribers get higher request thresholds and extended context windows.
I have curated best resources to get started with Gemini 2.5 Pro across its best use case:
Gemini 2.5 Pro for coding:
Gemini 2.5 Pro is particularly strong in coding tasks. This is due to its enhanced reasoning capabilities and has a massive context window of 1 million tokens. It can analyze entire codebases, debug complex issues, and generate production-ready code.
- Learn how to use Gemini for tasks like debugging, architectural recommendations, and implementing design patterns: Gemini API documentation
- DataCamp’s tutorial on set up of the Gemini 2.5 Pro API.
- Learn about Gemini 2.5 Pro integration with Cursor: FREE Gemini 2.5 Pro API: Testing Google’s New 1 Million Token Beast
- How to use Gemini to build products: tutorials by Julian Golden
Gemini 2.5 Pro for writing:
Gemini excels in generating high-quality written content by reasoning step-by-step and maintaining coherence across large contexts. I still think that Claude 3.7 Sonnet is better, but you can explore it for large context use cases.
Who is better than Nerdy Novelist to discuss using Gemini 2.5 Pro for writing? Here is his most updated take:
Gemini 2.5 Pro for solving complex math and data visualizations:
I found this interesting playlist that covers complex use cases like simulation, coding, and maths using Gemini 2.5 Pro:
Gemini AI communities and resources to make the most of Gemini 2.5 Pro
Gemini 2.5 Pro has received good reviews across the early adopters. To explore best practices and tricks, join these communities or explore resources I found:
- Communities: Explore the Gemini SubReddit, Google Gemini AI SubReddit, Gemini Apps Community, Gemini QnA Thread,
- Gemini AI resources by Google team for prompts, best practices, and use case exploration: Gemini for Work
- Detailed review of Gemini 2.5 Pro vs ChatGPT: I found this useful Reddit post on why a user switched back to ChatGPT from Gemini.
- Explore Gemini Advanced: its features, pricing plans, and potential use cases.
How are you using Gemini 2.5 Pro for free?
I think Gemini 2.5 Pro marks the end of basic coding. One can truly build apps and launch it too. Of course, one still requires professionals for proper deployment and maintenance. People are building interesting games, re-doing their websites, analyzing large data, and much more.
Take a look at its release notes, and you will see that there is more to come:
I am excited to use more of Gemini and hope for a good integration with Google NotebookLM.
How are you using Gemini 2.5 Pro now that is is free? Share it 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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