OpenAI released its fourth model upgrade of 2026, as it seeks to compete against Anthropic and Google in the generative AI race and make headway in the sought-after enterprise market.
The vendor introduced GPT-5.5 on April 23, a model update it said excels at coding, introduces fewer security problems and supports agentic autonomy and reasoning. The model understands what a user is trying to do more quickly and is proficient in writing and debugging code, conducting online research, analyzing data and creating documents. It is also token-efficient, using fewer tokens to perform the same task as GPT-5.4. The upgraded model is now available to Plus, Pro, Business and Enterprise users in ChatGPT and Codex. GPT-5.5 Pro and GPT-5.5 Thinking versions are available to Pro, Business and Enterprise users in ChatGPT.
GPT-5.5, like recent model releases from other generative AI vendors, focuses on advancements in reasoning and coding. OpenAI archrival Anthropic, in its latest release, Claude Opus 4.7, improved coding by providing better memory across sessions and long-running tasks, with greater consistency and higher accuracy than previous iterations. Google also focused on advanced coding in Gemini 3.1 Pro.
“Software engineering is heavily touted because it’s the fastest growing domain for generative AI today,” said Arun Chandrasekaran, an analyst at Gartner. “OpenAI wants to be seen as a very strong competitor in that space.”
He added that, beyond coding, OpenAI has also made progress in tool usage (which enables custom agent building) and token efficiency, making GPT 5.5 more inference friendly.
Coding Improvements
On the coding front, GPT-5.5 shows a reduction in the number of bugs or vulnerabilities per line of code, according to Joe Tyler, an AI researcher at Sonar, a company that specializes in code review. After running GPT-5.5 through its LLM evaluation framework, Sonar found that GPT-5.5 produces code faster than an unaided team. Still, its main strength is that the model isn’t as security averse as previous generations, Tyler said.
“If you sum together several bugs and vulnerabilities that this model produces, it’s lower than any other model in the top tier of coding,” Tyler said. But he said that the Anthropic models Opus 4.5 and 4.6 have simpler code and provide more useful developer comments.
GPT-5.5 also appears to fall behind Anthropic’s models on concurrency bugs, Tyler said. These are software errors that occur when a program performs multiple tasks simultaneously. While Opus 4.7 avoids those types of problems most of the time, this issue still needs attention in GPT-5.5.
“It is very strong in that it doesn’t produce very many bugs and vulnerabilities on average, but it still does introduce bumps and vulnerabilities,” Tyler continued, referring to GPT-5.5 and adding that enterprises looking to use the model must have a verification process in place to monitor the code.
A Need for Evaluation
Enterprises planning to use the model using an API should also have an effective evaluation process, Chandrasekaran said.
“You have to test your existing prompt libraries, your existing APIs and compatibility with these models,” he said, especially with OpenAI releasing updates frequently.
Nevertheless, GPT-5.5 is a good model that enterprises should find well-suited to their coding needs, said Bradley Shimmin, an analyst at Futurum Group.
He said that OpenAI’s focus on integrated reasoning will help enterprises handle difficult tasks autonomously, and its focus on token efficiency is also important. So, enterprises will be able to do more with fewer tokens, which is ultimately less costly.
“We are really starting to enter a period where model makers … and platform makers for AI are all starting to center on supporting these highly autonomous, long-running processes that are complex,” Shimmin said. “You need something mobile. You need something efficient for token utilization, and something that can work over a very sizable, sometimes complex, context window during that period of running. They’re good moves in that regard.”
