OpenAI dropped GPT-5.4 on March 5, and after spending three weeks putting it through its paces, I have thoughts. Lots of them. This isn’t just an incremental update — it’s a genuinely different experience from GPT-5.2, and in some ways, it changes what you can realistically expect from an AI model.
So let me break down what’s actually new, what works, what doesn’t, and whether the pricing makes sense for your workflow.
The 1 Million Token Context Window Is Real
GPT-5.4 ships with a 1.05 million token context window. That’s not a typo. You can feed it entire codebases, full research papers, or months of conversation history and it’ll actually track the context coherently.
I tested this by dropping a 280-page technical manual into a single conversation and asking specific questions about sections near the beginning, middle, and end. It nailed about 90% of them without any noticeable degradation. With GPT-5.2’s 128K window, I’d have to chunk that document into pieces and lose cross-reference ability.
The practical impact here is huge for developers, researchers, and anyone dealing with long documents. You’re spending less time on prompt engineering workarounds and more time on actual work.
Tool Search: The Sleeper Feature Nobody’s Talking About
Here’s where it gets interesting. GPT-5.4 introduces something called Tool Search — a new architecture that lets the model work with large numbers of tools without stuffing all their definitions into the context window upfront.
Instead, the model gets a lightweight list of available tools. When it needs one, it dynamically looks up that tool’s full definition. OpenAI says this reduced total token usage by 47% while maintaining the same accuracy. If you’re building agents or complex tool-use workflows, this is a pretty big deal for both cost and performance.
Native Computer Use — Yes, It Controls Your Browser
GPT-5.4 is OpenAI’s first model with native computer use capabilities. It can directly control your browser and desktop, and according to OpenAI, it actually outperforms human baselines on the OSWorld-Verified and WebArena benchmarks.
I tried it for some basic tasks — filling out forms, navigating multi-step web workflows, extracting data from dashboards. It worked surprisingly well for straightforward tasks but still stumbled on anything requiring complex visual interpretation or multi-tab coordination.
Accuracy Improvements That Actually Matter
OpenAI claims GPT-5.4 is 33% less likely to make individual factual errors compared to GPT-5.2, and overall responses are 18% less likely to contain any errors at all. It also scored 83% on OpenAI’s GDPval test for knowledge work tasks.
In my testing, the hallucination reduction is noticeable. I asked it about niche technical topics where GPT-5.2 used to confidently make stuff up, and 5.4 was much more likely to hedge or admit uncertainty. That’s progress.
Three Variants: Which One Should You Pick?
GPT-5.4 comes in three flavors: Standard, Thinking, and Pro. Standard is your everyday workhorse. Thinking adds chain-of-thought reasoning for complex problems — think math, logic, code debugging. Pro is the heavy hitter optimized for maximum performance on difficult tasks.
For most people, Standard covers 80% of use cases. I’d only reach for Thinking or Pro when you’re dealing with multi-step reasoning or need the absolute best accuracy on critical tasks.
Pricing: How Does It Stack Up?
OpenAI hasn’t slashed prices here — GPT-5.4 is positioned as a premium model. But the Tool Search feature alone can cut your API costs nearly in half for tool-heavy workloads, which partially offsets the per-token pricing.
Compared to Claude Opus 4.6 and Gemini 3.1 Pro, GPT-5.4 sits in a similar price tier but offers that massive context window advantage. If you’re choosing between them, it really comes down to what matters most for your specific use case.
The Bottom Line
GPT-5.4 is a solid step forward. The million-token context window and Tool Search are genuine innovations, not just marketing fluff. The accuracy improvements are measurable. Computer use is promising but still early.
If you’re already on GPT-5.2, upgrading is a no-brainer. If you’re on Claude or Gemini, it’s worth testing GPT-5.4 on your specific workflows before making a switch — each model still has its strengths depending on the task.