GPT 5.4 is our most advanced model so far. It enables faster, more accurate results in the API and Codex, helping people and teams make better decisions, increase productivity, and streamline processes.
In most cases, GPT-5.4 is the default choice for general tasks and coding, chosen to simplify complex workflows, save time on software engineering, enhance reasoning, improve writing quality, and open tools, all with one model.
This article presents the standard features of the GPT-5 models and shows practical ways to make the most of GPT-5.4.
Key Improvements
GPT 5.4 offers several improvements over the previous GPT 5.2 model:
- Experience sharper coding, better document understanding, smarter audio, and more reliable instruction following.
- Enhanced image perception lets users analyze visuals more accurately. It also helps manage multimodal workflows more easily.
- Users can complete long-running tasks faster than before. They can also execute multi-step agent workflows more reliably.
- More efficient token use reduces costs and improves end-to-end performance for heavy tool-based workloads.
- Faster, smarter web search uncovers hard-to-find information, saving time and simplifying research.
- Streamlining the handling of many documents or spreadsheets boosts productivity across customer service, analytics, and finance workflows.
Developers produce production-ready code and polished interfaces faster and more consistently, with fewer prompts for refinement.
For agent-based tasks, GPT 5.4 completes multi-step processes faster. It often uses fewer tokens and tool calls. This makes agent-based approaches more responsive and reduces the cost of operating complex workflows at scale in API and Codex.
New Features in GPT 5.4
Like its predecessors, GPT 5.4 offers flexible tool options, control over explanation detail, and curated tool lists. Now enjoy new features that make building agent systems easier, help manage more information, and ensure reliable automation.
- With the API tool search, you can seamlessly browse tools across vast ecosystems. Only what you need. Work smarter with fewer tokens and on-point choices. Discover more in the tool search guide.
- 1M token context window: GPT‑5.4 can handle up to 1M tokens. This makes it easier to analyze entire codebases and large sets of documents, or to run agent processes in a single request. You can read more in the “1M context window” section.
- Interact directly with software for the first time. Agents can now complete, check, and fix tasks faster in a complete build, run, and verify. Check out the computer use guide for more.
- Power through longer processes. Keep vital content thanks to GPT-5.4’s native compaction support.
Meet the Models
For most tasks and coding, GPT-5.4 is your new go-to model. It now replaces GPT-5.2. GPT-5.4 Codex and ChatGPT users get GPT-5 chat (latest) by default. Need better answers? GPT-5.4 Pro Raw hardness offers extra compute for data-fest challenges.
Prefer a compact model try GPT-5 Mini for streamlined performance.
Ready to choose and weigh these trade-offs to find your perfect match:
| Variant | Best for |
| GPT 5.4 | General purpose work including complex reasoning, broad word knowledge and code-heavy or Code heavy multistep agentic tasks |
| Gpt 5.4 Pro | Tough problems that may take longer to solve and need deeper reasoning |
| GPT 5 mini | Cost-optimized reasoning and chat; balancesspeed, cost, and capability. |
| GPT 5 nano | High-throughput tasks, especially straightforward instruction-following or classification |
Lower Reasoning Effort
The reasoning effort setting determines how many reasoning tokens the model uses before responding. Older models like O3 only offered low, medium, and high options. “No” meant faster, less thoughtful responses, while I meant longer, more reasoned answers.
From GPT 5.2 on, the lowest setting is called NUM, which enables faster responses. This is now the default in GPT 5.2 and later; to increase model reasoning, raise the setting to medium and observe the changes.
When reasoning effort is set to none, prompts become more important. For better reasoning, even at the default setting, ask the model to think or list its steps before answering.
Verbosity
Verbosity controls how many output tokens the model produces. Fewer tokens make responses quicker. Reasoning style remains mostly unchanged, but responses will be briefer, which can end or hurt depending on your needs. Use high verbosity for detailed explanations or major code changes. Use low for brief answers or simple code.
- High verbosity is useful for detailed document explanations or major code refactoring.
- Low verbosity is best for short answers or simple code, such as SQL queries. GPT-5 supports high, medium, and low settings. In GPT 5.4, you can still adjust verbosity, with medium as the default.
With GPT 5.4, medium and high robustness produce longer, more organized code with explanations. Semicolon, more,e generates shorter code with little extra commentary.
GPT 5.4 is designed to solve problems by reasoning through them.
Models like GPT-5.4 solve problems step by step. They create an internal chain of thought as their reasoning; for best results, send these reasoning steps back to the model. This prevents the same reasoning from being repeated and keeps the conversation aligned with the model’s training. In conversations with multiple turns, using previous_response_id will automatically include earlier reasoning steps. This is especially useful when using tools. For example, if a function call needs another wrong group, you can use the previous_response_id, or alternatively, add the reasoning steps directly to the input.
Source: Using GPT-5.4
