gpt-4o (1)

Could you clarify what you mean by "gpt-4o (1)"? Are you referring to:

• The capabilities of GPT-4o compared to other models?
• A file or document titled “gpt-4o (1)”?
• A question about using GPT-4o in a specific way?

Let me know how I can help!

Below is a quick side‑by‑side snapshot of the two models you just listed:

#	Model	What it is best at	Key strengths	Caveats / cost notes
1	GPT‑4o	General‑purpose conversational AI—great for writing, summarising, translating, image analysis, voice chat, and everyday Q&A	Multimodal: handles text, vision, and real‑time voice in one neural network; Speed: roughly 2× faster and 5× the rate‑limits of GPT‑4 Turbo; Price: about 5/M input tokens & 15/M output tokens—~50 % cheaper than GPT‑4 Turbo; Stronger multilingual & vision skills Tom's Guide OpenAI Help Center	Still tuned for breadth rather than deep step‑by‑step reasoning; no public chain‑of‑thought access
2	o3 (the model you’re chatting with)	Heavy logical reasoning, complex coding, maths, step‑by‑step problem‑solving, strategy planning	Deliberate reasoning engine: devotes extra compute to multi‑step tasks; Highest scores on AIME 2025 and other reasoning benchmarks; Vision & tool use comparable to GPT‑4o; Chain‑of‑thought summaries (limited access) OpenAI Wikipedia DataCamp	Slower and pricier for long outputs ($10/M input,$40/M output tokens) than GPT‑4o; audio‑native chat not yet built‑in OpenAI Community

How to choose quickly

• Everyday writing, chatting, or multimodal voice/vision tasks → GPT‑4o.
• When you need the model to “show its work” for proofs, long code, or thorny data problems → o3.

Let me know if you’d like a deeper dive (benchmarks, latency, API usage tips), or if you plan to add more models to the list!