o1 - AI Model Guide

OpenAI o1 is a reasoning-first AI model designed for complex, high-stakes problems in math, science, law, and coding. Unlike GPT-4, which prioritizes speed and fluency, o1 spends more compute time thinking through problems step-by-step, producing more accurate and verifiable outputs rather than fast approximations.

OpenAI o1 achieves 76% accuracy on the GPQA Diamond benchmark, which tests PhD-level scientific reasoning. It also scores in the 89th percentile on Codeforces competitive programming evaluations, making it one of the strongest publicly available models for both scientific and coding tasks.

OpenAI o1 excels at complex multi-step reasoning tasks including advanced mathematics, scientific research, legal and medical analysis, competition-grade coding, data science workflows, and technical writing validation. It is best used when accuracy is critical and the cost of an incorrect answer is high.

You can run OpenAI o1 directly on CRAISEE via the Replicate provider. The model supports a configurable reasoning_effort parameter, letting you balance depth of reasoning against response time. With over 18,906 runs on the platform, o1 is CRAISEE's top choice for professional and research-grade AI tasks.

The reasoning_effort parameter in OpenAI o1 lets users control how much compute time the model spends reasoning before responding. Higher effort produces more thorough, accurate answers for complex problems, while lower effort speeds up responses for simpler tasks — giving users flexibility based on their accuracy and latency requirements.

Yes. OpenAI o1 is designed for legal and medical analysis that requires precise, nuanced interpretation of complex source material. Its deliberative reasoning approach and high-reliability output — evaluated under strict 4/4 accuracy metrics — make it suitable for professionals who need consistently correct, verifiable answers rather than probabilistic approximations.

OpenAI o1 scores in the 89th percentile on Codeforces, a competitive programming platform used to benchmark elite coders. It supports competition-grade coding, complex debugging, and root cause analysis across interdependent systems, making it one of the most capable AI models available for advanced software engineering challenges.

Yes. OpenAI o1 achieves 76% accuracy on GPQA Diamond, a benchmark designed to test PhD-level scientific problem solving. It supports research design, statistical reasoning, model evaluation, and technical writing validation — making it a strong tool for researchers who need reliable, high-accuracy AI assistance across STEM disciplines.