GPT-5.4: A new AI model for smarter and faster professional tasks.

Artificial intelligence models are evolving rapidly, transforming from simple chat assistants into powerful tools capable of handling complex professional tasks. GPT-5.4 This marks a significant step in this evolution, integrating advanced reasoning capabilities, coding expertise, and agent-driven workflows into a single model. 

This new model is now enabled in... ChatGPT, API และ Codex It is specifically designed to support developers, professionals, and organizations that use AI for real-world tasks, from coding and data analysis to documentation and managing complex workflows. The system is designed to deliver faster, more accurate, and reliable results by minimizing repetitive interactions. 

For users who require even higher performance for complex tasks, there is also an advanced version called... GPT-5.4 Pro Also available for additional use. 

Why was GPT-5.4 built for real-world professional use? 

Understanding the power of GPT-5.4. 

GPT-5.4 integrates several advancements from previous models into a single architecture, including stronger reasoning capabilities, advanced coding capabilities, and improved interoperability with external software tools and systems. 

These developments enable the models to assist with tasks commonly encountered in professional work environments, such as: 

• Working with spreadsheets and analyzing data. 
• Creating structured presentations and documents. 
• Writing and debugging complex code. 
• Doing in-depth research 
• Managing multi-stage workflows between different applications. 

Instead of simply answering questions, this model is designed to help. Complete the work efficiently. This makes it an essential tool for knowledge-related work in the modern era. 

Significant improvements in GPT-5.4. 

This latest model features several key innovations that make it even more suitable for professional use. 

1. Advanced reasoning and intellectual work.

This model improves reasoning capabilities compared to previous systems and increases consistency in handling real-world work tasks. 

In the internal evaluation GDPval This model, which measures the performance of AI in knowledge-based tasks across various professions, scored the highest in the industry. 

These results demonstrate that the model is capable. Providing work quality that is equivalent to or better than that of industry experts. For structured knowledge-based tasks. 

2. The ability to use a computer directly.

One of the most important innovations is Computer-Use Capabilities

For the first time, a generic model can interact directly with the computer and software environment, enabling AI agents to perform various tasks, such as:

• Website navigation
• Application control
• Conducting workflows across multiple tools.
• Interacting with the interface via screenshots.

The system can generate code to control the browser using frameworks such as... Playwright Or it can simulate the use of a mouse and keyboard.

The performance test results show clear progress.

These results demonstrate that the model is capable. Perform complex computer workflows more reliably. And in some cases, they even perform better than human standards. 

3. Powerful coding skills.

This model brings cutting-edge coding capabilities. GPT-5.3-Codex Let's integrate them and expand their capabilities to support longer development workflows. 

Developers can use this model to...

• Writing complex code in multiple languages.
• Debugging and improving the code of an existing project.
• Create a full-stack application.
• Automate the process of testing and verifying code.

In an environment like Codex The user can enable the mode. /fast To increase the maximum token processing speed. 1.5 times This allows developers to debug and improve code more quickly.

In addition, the model has outstanding capabilities in this task. Frontend Development This allows for the creation of user interfaces that are both practical and aesthetically pleasing.

GPT-5.4 with Agent workflow.

How does GPT-5.4 enable AI agents to perform advanced tasks?

Modern AI systems are evolving towards a system of operation. Agent It can handle multi-step workflows autonomously, and GPT-5.4 is designed to suit this type of environment.

With maximum contextual support. 1 million tokens The model can

• Planning an event
• carry out
• Check the results

For complex and time-consuming tasks.

Examples of use include:

• Processing large documents
• Coordination of multiple APIs and tools.
• Multi-step automation
• Managing long-term software development workflows.

This capability enables businesses and developers to create more reliable automation systems.

Better collaboration with tools

Using tools and finding tools more intelligently.

Interacting with external tools used to be challenging for AI because it required including the definitions of all the tools within the context of the commands.

A new ability called Tool Search has changed this approach

Instead of loading all tool definitions at once, the model will only receive... Brief list of tools And when necessary, the system will dynamically retrieve the details of that tool during operation.

This system offers several advantages.

From the test as well MCP Atlas benchmark This method can reduce token usage by... 47% While maintaining the same level of accuracy.

Improved workflow control in ChatGPT.

Real-time planning with GPT-5.4

In ChatGPT mode. Thinking A new feature has been added that allows the model to display its reasoning plan before generating the final answer.

This allows users to:

• It's possible to see how the model plans to solve the problem.
• Instructions or approaches can be adjusted while the model is running.
• Guide the results to best match your needs.

For complex professional tasks, this interactive workflow reduces the need to repeatedly send commands or frequently revise answers.

Furthermore, the model can maintain the context of conversations for longer periods, making it easier to handle large projects or multi-stage workflows.

A theme park simulation game built with GPT-5.4 from a short prompt, using Playwright Interactive for browser-based game testing, and utilizing a visualization system to generate an isometric graphic resource set.

The game includes various systems such as:

• Tile-based walkway design
• Creating play equipment and decorations.
• Guest pathfinding system
• Queuing for rides
• The operating cycle of the player

Meanwhile, indicators for amusement parks, such as...

• Game money
• number of visitors
• Satisfaction
• Cleanliness
• Amusement park review score

The number of visitors will increase or decrease depending on the park's layout and visitor behavior.

Playwright is used to automate browser game testing, following steps such as:

• Building and expanding theme parks 
• Placing and removing walkways or play equipment. 
• Monitoring camera movement. 
• Verify that visitor counts, queue system, player status, and UI values ​​are correctly updated over multiple playthroughs. 

Example Prompt 

Prompt: Use $playwright-interactive and $imagegen. Create an interactive isometric theme park simulation game that I can build and navigate in the browser. Use imagegen to establish the overall visual vision and generate the game’s assets, including rides, paths, terrain, trees, water, food stalls, decorations, buildings, icons, and UI illustrations. The world should feel cohesive, polished, and visually rich, with a premium art direction that works well from an isometric perspective. Let me place and remove paths, add attractions, position scenery, and move around the park smoothly while monitoring guest activity, ride status, and park growth. Include believable guest movement, simple park management systems like money, cleanliness, queueing, and happiness, and make the experience feel playful, clear, and complete rather than like a rough prototype. Prioritize charm, readability, and strong game feel over realism. 

When play testing, be sure to build and expand a park through several rounds of play, verify that placement and navigation work smoothly, confirm that guests react to the park layout and attractions, and ensure the visuals, UI, and interactions feel stable and cohesive.

Real world applications

Organizations and developers can apply this technology in many areas.

software development

AI can assist in writing, testing, and debugging code, as well as interacting directly with the development environment.

Information and knowledge-related work.

Experts can use AI to:

• Analyze data in a spreadsheet.
• Create a report
• Extract insights from complex datasets.

Automation and AI Agents

Businesses can create AI agents that automate tasks across multiple applications, reducing manual work and increasing efficiency.

Research and Analysis

The enhanced ability to conduct in-depth web research allows users to find and summarize specialized information more quickly.

Conclusion

The evolution of AI models today focuses on... Increasing real work efficiency More than just a conversation assistant.

By combining the abilities of

• advanced reasoning
• A powerful tool for writing code.
• The ability to use a computer directly.
• Efficient connection of external devices.

GPT-5.4 is therefore considered a significant step in AI systems that can truly help with professional-level work.

In the future, AI models like this will play a crucial role in modern digital workflows, enabling professionals to work faster, create more sophisticated software, and automate many organizational processes more efficiently.