GPT-4o vs OpenAI o1 (2026)

o1 scores 96.4% on MATH vs GPT-4o's 76.6% — a massive 20-point gap. o1 was purpose-built for hard reasoning and outperforms every general model on mathematics, logic puzzles, and step-by-step problem solving.

o1 scores 92.4% on HumanEval vs GPT-4o's 90.2%. A narrow benchmark gap, but in practice o1 handles complex algorithmic problems and tricky debugging scenarios more reliably — especially when the solution requires multiple reasoning steps.

o1 scores 78.3% on GPQA (graduate-level science questions) — significantly ahead of GPT-4o. For PhD-level reasoning in physics, chemistry, or biology, o1 is in a different league.

GPT-4o costs $2.50/1M input tokens vs o1's $15.00/1M — 6x cheaper. For high-volume API usage, this difference is enormous. o1 is best reserved for tasks that genuinely need its reasoning power.

GPT-4o responds quickly with low latency. o1 'thinks' before responding — extended reasoning chains can take 30–60 seconds or more for hard problems. For interactive chat or real-time applications, GPT-4o is the only practical choice.

GPT-4o is significantly better at creative tasks — stories, marketing copy, scripts, brainstorming. o1 is optimised for systematic reasoning, not open-ended creativity.

For email drafting, summarising documents, answering questions, and everyday tasks, GPT-4o is faster, cheaper, and just as capable as o1. o1's reasoning overhead adds no value for simple tasks.

o1 has a 200K token context window vs GPT-4o's 128K. For processing very long documents or multi-file codebases, o1 can fit more context in a single prompt.

Both accept image inputs and handle visual reasoning. GPT-4o has a slight edge on visual creativity tasks; o1 handles visual reasoning problems (geometry, charts, diagrams) more precisely.

Both models have access to Bing-powered web browsing in ChatGPT. Via API, neither has real-time web access by default — you need to add a search tool.