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March 1, 2025
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8
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ChatGPT-4.5 vs Google Gemini: Which AI Model Performs Better?
George Miloradovich
Researcher, Copywriter & Usecase Interviewer
ChatGPT-4.5 and Google Gemini are two leading AI models, each tailored for different needs. Here’s a quick breakdown:
| Feature | ChatGPT-4.5 | Google Gemini |
|---|---|---|
| Primary Strength | Text-based tasks & research | Multimodal data processing |
| Accuracy Rate | 80-85% | 90% |
| Integration | Microsoft ecosystem, APIs | Google Workspace |
| Context Window | 128,000 tokens | 1 million tokens |
| Response Speed | Slower during peak times | 15% faster than competitors |
| Cost (API Input) | $7.50/million tokens | $0.075/million tokens (Flash) |
Choose ChatGPT-4.5 for advanced text tasks and flexibility, or Google Gemini for real-time, multimodal data processing and Google Workspace compatibility. Both are powerful tools but cater to different automation needs.
ChatGPT-4.5 has reduced hallucinations by 37.1% and is capable of maintaining context even in complex workflows. On the other hand, Google Gemini achieves an impressive 90% accuracy, leveraging real-time data for its outputs.
"The first model that feels like talking to a thoughtful person to me. I have had several moments where I've sat back in my chair and been astonished at getting actually good advice from an AI." – Sam Altman, OpenAI co-founder and CEO
What sets these models apart isn’t just the quality of their text generation but also how they handle various types of inputs.
ChatGPT-4.5 shines in text-based tasks and now supports features like:
Meanwhile, Google Gemini processes multiple input types simultaneously, including text, images, video, and audio. For example, Gemini can analyze product images and suggest clothing combinations - a feature particularly helpful in fashion retail.
Integration capabilities are a key differentiator between the two platforms.
| Integration Feature | ChatGPT-4.5 | Google Gemini |
|---|---|---|
| API Access | Broad API suite, including Chat Completions, Assistants, and Batch APIs | Built-in integration with Google Workspace |
| Data Processing | Supports structured outputs, vision tasks, and streaming | Real-time data handling with multilingual support |
| System Integration | Offers function calling, prompt caching, and evaluation tools | Deep integration with the Google ecosystem |
| Performance Metrics | 15–20% error rate with creative flexibility | 90% accuracy and faster responses |
For workflow automation, ChatGPT-4.5’s extensive API and function-calling features make it ideal for custom setups, especially when paired with platforms like Latenode. In contrast, Gemini’s seamless integration with Google Workspace makes it a natural fit for workflows centered around Google tools.
ChatGPT-4.5 operates on a massive 1.7 trillion parameters, offering extensive customization for technical users. Meanwhile, Gemini’s real-time, multimodal capabilities cater to diverse data analysis needs, particularly in Google-based environments.
Both models perform well in enterprise tasks, but they shine in different areas. According to Box, GPT-4.5 improved enterprise document Q&A accuracy by 4 percentage points. In specific tests, GPT-4.5 delivered:
"Particularly potent for enterprise use-cases, where accuracy and integrity are mission critical… our testing shows that GPT-4.5 is one of the best models available both in terms of our eval scores and also its ability to handle many of the hardest AI questions that we have come across." – Box
Google Gemini, on the other hand, maintains a steady 90% accuracy rate across tasks. Its ability to leverage extensive data resources ensures dependable performance, especially for time-sensitive business needs. With quality established, it’s time to look at response speed.
Response speed is vital for real-time applications. Gemini 2.0 Flash has doubled the speed of its earlier version while maintaining accuracy. This improvement allows for interactions that feel more natural, making it ideal for customer service and real-time analytics.
| Performance Metric | Google Gemini | ChatGPT-4.5 |
|---|---|---|
| Response Speed | 15% faster than competitors | Variable during peak times |
| Real-time Processing | Built-in capability | Limited access |
| Concurrent Processing | Smoothly handles multiple tasks | May slow under heavy load |
| Context Window | 32,768 tokens | 128,000 tokens |
System requirements play a big role in deployment and performance. Google Gemini uses TPUv5 chips with 16,384 running in parallel, ensuring efficient processing and consistent accuracy. This setup supports its ability to maintain a 90% accuracy rate.
ChatGPT-4.5, built on GPT-4 infrastructure with 175 billion parameters, excels in advanced language tasks but demands significant computing resources. This can impact response times during peak usage periods.
Key factors for deployment include:
"Everything is a little bit better and it's awesome, but also not exactly in ways that are trivial to point to." – Andrej Karpathy, Former OpenAI Researcher
ChatGPT-4.5, when integrated with Microsoft's tools, is great for automating text-heavy tasks. Think report writing, managing customer responses, drafting emails, or summarizing meetings. On the other hand, Gemini is built to handle both structured and unstructured data. It automates tasks like data entry, creating financial models, and even directly working with spreadsheets.
Latenode's low-code platform provides flexible integration options for both ChatGPT-4.5 and Gemini. ChatGPT-4.5 integrates easily through OpenAI's assistant tools using Latenode’s visual builder. Meanwhile, Gemini taps into Google's AI via a comprehensive app ecosystem. This enables automated workflows for data processing, business rules, and real-time triggers across over 1,000 apps. These integrations lay the groundwork for advanced real-time data insights.
Google Gemini's connection to BigQuery has redefined real-time analytics for businesses. For instance, in an e-commerce fraud detection case, transaction data is streamed via Pub/Sub into BigQuery. Vertex AI then analyzes these transactions live, flagging suspicious ones on Looker dashboards. Gemini also streamlines data analysis with tools for cleaning data, creating interactive visualizations, forecasting in real time, and spotting anomalies. For cost comparison, Gemini 1.5 Flash charges $0.90 per million tokens, while GPT-4 costs $7.50 for the same input size.
"Gemini is the most 'capable' model they've ever built." – Demis Hassabis, CEO and Co-Founder of Google DeepMind
ChatGPT-4.5, however, focuses on precision and reducing errors in data analysis. While it doesn’t have Gemini’s multimodal capabilities, it shines in delivering accurate, language-driven insights. This makes it particularly useful for qualitative research and creating detailed reports.
You can access ChatGPT-4.5 through OpenAI's web interface for quick interactions. Business users can collaborate using Teams workspaces, while integrating custom APIs may require some technical know-how.
Google Gemini works seamlessly with Google Workspace tools like Gmail, Google Sheets, and Google Drive. If you're familiar with these apps, you can easily use Gemini's AI assistant features. Setting everything up correctly is key to using these tools effectively in automated workflows.
Once you're set up, it's important to review the costs to make sure the tools fit your budget.
After gaining access, understanding the pricing options is essential for managing expenses.
| Feature | ChatGPT-4.5 | Google Gemini |
|---|---|---|
| Basic Access | Free tier with GPT-4o mini | Free tier with Gemini Code Assist |
| Professional | $20/month (Plus) | $20/user/month (Business) |
| Team Features | $25/user/month (annual) | $30/user/month (Enterprise) |
| API Usage (Input) | $75 per million tokens | Gemini 1.5 Pro: $1.25 per million tokens, or Gemini 1.5 Flash starting at $0.075 per million tokens |
| API Usage (Output) | $150 per million tokens | Gemini 1.5 Pro: $5.00 per million tokens, or Gemini 1.5 Flash at $0.30 per million tokens |
The Enterprise plan offers higher usage limits, improved privacy, and dedicated support. For businesses with heavy API needs, Google Gemini's Gemini 1.5 Flash option starts as low as $0.075 per million input tokens.
Data security is a top priority for business users. ChatGPT-4.5's Enterprise plan includes advanced privacy features and dedicated support.
Google Gemini relies on Google Cloud's security protocols, which align with organizational policies.
"AI coding tools are becoming essential for developers and should be accessible to everyone, regardless of their financial resources."
– Ryan J. Salva, Senior Director of Product Management, Google Cloud
For developers, the free version of Gemini Code Assist is a standout, offering up to 180,000 code completions per month. This makes it a great choice for teams working on automation projects.
When comparing ChatGPT-4.5 and Google Gemini, each model shines in areas that matter for business automation. ChatGPT-4.5 stands out for its strengths in creative tasks and ethical reasoning, while Gemini is recognized for its technical accuracy and ability to deliver precise data insights.
One notable technical difference is their token capacity. ChatGPT-4.5 operates with a 128,000-token context window, while Gemini supports up to 1 million tokens. This difference impacts how they handle large-scale data in business workflows. Additionally, Gemini integrates seamlessly with Google Workspace, whereas ChatGPT-4.5 offers more flexibility with third-party platforms like Zapier.
Your choice should align with your specific needs:
Opt for ChatGPT-4.5 if you need:
Go with Google Gemini if you require:
"We have basically come to a point where most LLMs are indistinguishable on qualitative metrics." – Subbarao Kambhampati, AI professor at Arizona State University
These distinctions highlight how each model serves different automation needs.
AI automation is advancing at a fast pace, and both ChatGPT-4.5 and Google Gemini are contributing to this growth. ChatGPT-4.5 is making strides in areas like agentic planning and multi-step coding workflows, with improvements in factual accuracy and reduced hallucination rates.
Meanwhile, Google Gemini is pushing boundaries with faster processing - delivering responses about 15% faster than competitors - and leveraging its large context window for handling complex, data-heavy tasks. Deciding between the two will depend on your current technical setup and how their evolving features align with your business goals.
