OpenAI has recently introduced GPT-5, a new generation of models for both ChatGPT and its API, expanding its capabilities with a range of specialized variants tailored to different uses—from quick conversations to complex problem-solving, including versions specifically optimized for developers. The latest system card released by OpenAI provides clarity and establishes connections with previous models.
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GPT-5 Model Variants
Although GPT-5 appears to be a single entity, OpenAI has actually segmented it into multiple versions to accommodate varying needs for cost, speed, and analytical depth. Here are the six officially documented variants:
- gpt-5-main: the flagship model. It balances speed and response quality, suitable for a wide array of applications from daily dialogue to technical queries. It serves as the foundational model used in ChatGPT and through the API.
- gpt-5-main-mini: a lighter, more cost-effective version of gpt-5-main, designed to lower costs while maintaining a high level of relevance. It’s perfect for high-volume applications or those requiring very low latency.
- gpt-5-thinking: tailored for “deep thinking.” This variant takes more time to provide responses but delves deeper into possibilities before delivering an answer. It’s ideal for complex problems or tasks needing multi-step reasoning.
- gpt-5-thinking-mini: a balance between cost, speed, and depth of analysis. This model retains some of the deep reasoning capabilities of the “thinking” variant but requires fewer resources.
- gpt-5-thinking-nano: the ultra-compact version of the reasoning model. Extremely fast and lightweight, it is mainly aimed at developers using the API where cost and speed are prioritized over depth.
- gpt-5-thinking-pro: the premium model. Used in ChatGPT Pro, Team, and Enterprise, it builds on the “thinking” model but utilizes more computing power to provide longer, more detailed, and nuanced responses.
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GPT-5 is not just about surpassing previous models in benchmarks or responding faster: it is significantly more effective for real-world queries. We’ve made major advances in reducing delusions, enhancing instruction adherence, reducing complacency, and we have improved GPT-5’s performance in three of ChatGPT’s most common applications: writing, coding, and health.
Matching Old and New Models from OpenAI
With the introduction of GPT-5, all previous models are phased out from ChatGPT. To aid this transition, OpenAI provides a clear mapping table that correlates its old models to the new GPT-5 variants (see image one). This initiative helps users and developers quickly identify which new model corresponds to the old ones they used.
Here are the mappings provided:
- GPT-4o = gpt-5-main
- GPT-4o-mini = gpt-5-main-mini
- o3 = gpt-5-thinking
- o4-mini = gpt-5-thinking-mini
- GPT-4.1-nano = gpt-5-thinking-nano
- o3 Pro = gpt-5-thinking-pro
These mappings facilitate the adoption process as they allow for the migration of projects or usage habits to GPT-5 while maintaining similar or improved performance levels with the latest optimizations.
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Jordan Park writes in-depth reviews and editorial opinion pieces for Touch Reviews. With a background in UI/UX design, Jordan offers a unique perspective on device usability and user experience across smartphones, tablets, and mobile software.