The number of different models available from OpenAI has grown rapidly, and their naming conventions—well—are anything but intuitive. Between versions like GPT-4, GPT-4o, GPT-4.1, and their various “mini” and “turbo” siblings, it’s easy to lose track of what each model actually offers. This comparison aims to bring clarity to the current landscape as of May 2025.
Each model is compared in terms of release date, model size, training data scope, pricing, multimodal capabilities, performance/latency characteristics (including context window), availability in ChatGPT, fine-tuning support, and notable benchmark performance. The table below summarizes the key details:
Footnotes: GPT-4 “Turbo” refers to a variant of GPT-4 optimized for speed/cost (essentially GPT-4o in Azure deployment). All pricing is for the OpenAI API (as of 2025) and is listed per 1K tokens (prompt vs completion); ChatGPT user-facing models do not charge per token but correspond to the same underlying models. Fine-tuning support “planned” indicates OpenAI’s stated intent to allow fine-tuning (e.g. GPT-4.1) once the model is stable. Benchmarks: MMLU = Massive Multitask Language Understanding; GSM8K = Grade School Math; HumanEval = coding problems. GPT-4 and newer models generally outperform older ones on these benchmarks, with GPT-4.1 setting new records in coding and long-context understanding. GPT-4 and GPT-4o have achieved parity or better on many academic and professional exams (for example, GPT-4 ranks in the top 10% on the bar exam vs GPT-3.5 in bottom 10% ). GPT-4o’s “Omni” multimodal architecture enabled integrated vision and audio processing , and GPT-4.1 further builds on this foundation with extreme context length and improved alignment for complex instructions. All models above (except GPT-4.5 preview) are generally available via OpenAI’s API, with availability in ChatGPT noted where applicable.
No comments yet