As competition in the field of artificial intelligence intensifies, OpenAI's next-generation large language model, GPT-5, has attracted significant attention. According to the latest information, GPT-5 is expected to be released in mid-2025 to late 2025, with a specific time possibly in August or later. This article compiles the latest updates on the parameters, features, and potential impact of GPT-5 based on online information, providing you with the most comprehensive preview.
Release Date and Development Progress
According to the roadmap published by OpenAI CEO Sam Altman in February 2025, GPT-5 is expected to be launched in mid-2025, possibly in August or later. In a recent interview, Altman stated that the release of GPT-5 will be later than GPT-4.5 (codename Orion, which was released on February 27, 2025), and emphasized it as a "frontier model," representing a major technological leap.
However, technical and resource challenges during development could lead to further delays. It has been reported that the training cost for GPT-5 (which may be codenamed Orion or Arrakis) exceeds $500 million, and it requires large-scale data centers, with a training period of at least six months. OpenAI also experienced internal turbulence, including executive departures, which may affect the development progress.
Parameter Scale and Technical Architecture
Although OpenAI has not yet disclosed the exact number of parameters for GPT-5, industry speculation suggests its parameter scale will significantly exceed that of previous models. Here are key details:
- Parameter Scale: GPT-4 is estimated to have about 1.5 trillion parameters, while GPT-5 may reach between 3 to 50 trillion parameters, depending on whether a mixture of experts (MoE) model is used. It has been reported that GPT-5 may use 20,000 NVIDIA GB200 chips or 150,000 H100 chips for training, supporting a model with up to 80 trillion parameters.
- Architecture Innovation: GPT-5 will integrate the capabilities of the GPT series and the o series (such as o1, o3), using a unified architecture to eliminate the need for users to switch models for different tasks. It may introduce graph neural networks (GNN) and enhanced attention mechanisms to improve language processing efficiency and understanding of complex situations.
- Training Data: GPT-5 is expected to use a larger and more diverse dataset, including public web data and private enterprise data, and may combine synthetic data to address data shortages. However, synthetic data may cause feedback loops, increasing the risk of "hallucinations."
Core Features and Improvements
GPT-5 is designed as a multimodal, unified intelligent system, aiming to provide a more efficient and accurate AI experience. Here are the expected highlights of its core features:
- Multimodal Capabilities: GPT-5 will further enhance its multimodal processing capabilities, supporting text, images, voice, and video input and output. Based on the voice and image processing foundation of GPT-4o, GPT-5 may integrate video processing functions, such as generating videos from text through OpenAI's SORA technology.
- Advanced Reasoning Capabilities: OpenAI emphasizes that GPT-5 will significantly improve chain-of-thought (COT) reasoning capabilities, excelling in multi-step logic and decision-making. Compared to the fast response of GPT-4o, GPT-5 will be better at handling complex problems, such as code generation and debugging in software engineering, and scientific tasks like mathematics and physics.
- Extended Context Window: The context window of GPT-4o is 128,000 tokens, while GPT-5 may support up to 5 million tokens, sufficient to process entire books or large corporate data, improving long-text processing capabilities.
- Reduced Hallucination: GPT-5 is expected to reduce the "hallucination" rate to below 10%, significantly improving the accuracy and reliability of outputs, especially in scientific and programming fields.
- Autonomous AI Agents: GPT-5 may introduce autonomous AI agent functionality, enabling it to perform real-world tasks such as managing emails, scheduling appointments, or completing shopping based on user preferences, reducing manual intervention.
- Canvas Workspace: Building on the Canvas feature of GPT-4o, GPT-5 will offer a more powerful interactive workspace, optimizing the experience for coding, mathematics, and step-by-step workflows.
Industry Impact and Application Prospects
The release of GPT-5 will have a profound impact on multiple fields:
- Software Development: Testers have reported that GPT-5's ability to generate and debug code in complex software projects surpasses Anthropic's Claude 4 Sonnet, potentially making it the preferred tool for developers.
- Scientific Research: In disciplines such as mathematics, physics, and biology, GPT-5's advanced reasoning capabilities will accelerate research processes, supporting complex data analysis and hypothesis validation.
- Business and Productivity: Through autonomous AI agents and personalized features, GPT-5 can optimize customer service, content creation, and daily task automation, enhancing enterprise efficiency.
- Education and Healthcare: GPT-5's multimodal capabilities and contextual understanding will revolutionize personalized learning in education and patient interaction and document processing in healthcare.
Challenges and Ethical Considerations
Despite its promising future, the development and deployment of GPT-5 face multiple challenges:
- Cost and Resources: High training costs and long data center construction cycles may limit OpenAI's parallel development capabilities.
- Ethics and Safety: Large-scale models may pose misuse risks, such as generating false information or simulating human behavior. OpenAI is conducting strict safety tests, delaying the release of certain features.
- Competitive Pressure: Competitors such as Anthropic's Claude series, Google's Gemini, and Meta's LLaMA are rapidly catching up, forcing OpenAI to find a balance between performance and reliability.
User Feedback and Community Expectations
On social media, developers have focused their expectations on the improvements in programming capabilities and reasoning performance of GPT-5. Some users mentioned on X that the early version of GPT-5 performed well in software engineering tasks, surpassing Claude Sonnet 4. However, some users are concerned about its high subscription cost and potential usage restrictions, similar to the adjustments made by Anthropic for the Claude Code Max plan, which may cause dissatisfaction.
Summary
GPT-5, as OpenAI's next-generation flagship model, is expected to significantly enhance the reasoning, accuracy, and practicality of AI through a larger parameter scale, a unified architecture, and multimodal capabilities. Despite facing multiple challenges such as cost, safety, and competition, its potential in programming, research, and business fields cannot be ignored. AIbase will continue to monitor the latest developments of GPT-5 and bring you the first-hand reports.
This article is compiled by the AIbase editorial team, integrating online information, striving to objectively present the latest developments of GPT-5.