OpenAI launches the groundbreaking Open Source GPT-OSS model: 120B performance comparable to o4-mini, developers can deploy it locally for free.

On August 5, 2025, ChatGPT creator OpenAI announced the launch of a new open source large language model, GPT-OSS, which is its first open source version since GPT-2. Key highlights include: the flagship gpt-oss-120b model performs nearly as well as OpenAI o4-mini in core inference benchmark tests and can run efficiently on a single 80GB GPU; the lightweight gpt-oss-20b model performs on par with o3-mini and supports deployment on edge devices with 16GB memory. This move will fundamentally change the way developers build AI applications, bringing breakthrough cost optimization and customization freedom to scenarios such as Crypto Assets trading Bots and data analysis platform.

OpenAI Breaks Through Open Source: Detailed Explanation of GPT-OSS Model Performance Parameters The intense competition in the field of artificial intelligence is bringing significant benefits to small and medium developers as well as end users. On August 5, 2025 (Tuesday), OpenAI officially released a brand new open source large language model GPT-OSS - this is the company's first open source model since GPT-2. Notably, the expected performance of the new model is anticipated to be on par with some of OpenAI's latest commercial versions. According to the official statement from OpenAI: "The gpt-oss-120b model performs comparably to OpenAI's o4-mini in core inference benchmark tests and can run efficiently on a single 80GB GPU; the gpt-oss-20b model reaches a similar level to the o3-mini in common benchmark tests, requiring only 16GB of memory to operate on edge devices."

Developer Revolution: From API Dependency to Autonomous Control This release means that anyone can run the model for free on their own devices. However, its more profound impact lies in the developer ecosystem—developers can freely integrate these models into applications and platforms, covering innovative scenarios such as Crypto Assets quantitative trading Bots, on-chain data analysis platforms, and more. Previously, developers needed to rely on OpenAI's API services to use AI features. Since it runs on OpenAI's cloud, the usage costs can quickly escalate. Moreover, developers have limited control over the models and can only use fixed versions. In contrast, open source AI models empower developers with key capabilities:

1. Model Modification Rights: Modify and fine-tune the model for specific scenarios (such as on-chain anomaly detection);
2. Data Autonomy: Training with proprietary data and customizing models in vertical fields (such as DeFi risk prediction) may be more accurate than cloud-based versions;
3. Cost Control: Local deployment eliminates API call fees, especially beneficial for high-frequency applications (such as real-time trading signal generation).

Open Source Ecosystem Landscape: Competitors like DeepSeek Face New Challenges GPT-OSS is not the only advanced large language model released in recent years. One of the most popular alternatives is the namesake model developed by the Chinese startup DeepSeek. OpenAI's entry into the open-source camp will significantly intensify competition in the high-performance LLM field, forcing all participants to continuously improve model efficiency and openness.

Conclusion: The Open Source Strategy of GPT-OSS and the Prospects of Web3 Applications OpenAI's open-source GPT-OSS marks a significant leap in the democratization of AI technology. For developers, this not only means breaking free from the cost shackles of commercial APIs but also opens a new era of customized AI applications. In the field of crypto assets and Web3, locally deployed high-performance models will give rise to smarter, more privacy-secure on-chain analysis tools, anti-MEV trading strategy engines, and decentralized AI agents. Despite the ecological foundation established by open source pioneers like DeepSeek, OpenAI, with its technological accumulation and brand effect, may reshape industry standards with this open source initiative. In the future, the focus of competition will shift towards model optimization usability, vertical scene adaptability, and community support strength. For developers seeking to build the next generation of Web3 applications, GPT-OSS offers an unprecedented technical leverage, the actual effectiveness of which will depend on the collaborative innovation vitality of the open source community.