"Together, these improvements mean higher-quality answers that arrive faster and stay relevant to the task at hand," the company states. Separately, OpenAI claims GPT-5.4 is its most factual model yet, noting, relative to GPT-5.2, it's 18 percent less likely to generate a response with any errors. Here's hoping it knows not to turn to Grokipedia for information, something its predecessor was known to do.
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After OpenAI released GPT-5.3-Codex (high) which performed substantially better and faster at these types of tasks than GPT-5.2-Codex, I asked Codex to write a UMAP implementation from scratch in Rust, which at a glance seemed to work and gave reasonable results. I also instructed it to create benchmarks that test a wide variety of representative input matrix sizes. Rust has a popular benchmarking crate in criterion, which outputs the benchmark results in an easy-to-read format, which, most importantly, agents can easily parse.
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