OpenAI时隔6年再度开源，两款推理模型，o4-mini级，手机和笔记本能跑

Core Insights - OpenAI has released two long-anticipated open-source models: gpt-oss-120b and gpt-oss-20b, both utilizing the MoE architecture for efficient deployment [1][2][3] - The gpt-oss-120b model can run efficiently on a single 80GB GPU, while the gpt-oss-20b requires only 16GB of memory for edge devices, providing local model options for AI applications [1][2][3] - The models have shown competitive performance in benchmark tests, with gpt-oss-120b performing similarly to OpenAI's o4-mini and gpt-oss-20b comparable to o3-mini [1][2][3] Model Specifications - gpt-oss-120b has 117 billion total parameters, activating 5.1 billion parameters per token, while gpt-oss-20b has 21 billion total parameters with 3.6 billion active parameters per token [29][30] - Both models support a context length of up to 128k tokens and utilize advanced attention mechanisms to enhance efficiency [29][30] Performance and Compatibility - The gpt-oss-120b model has achieved a record inference speed of over 3000 tokens per second, while gpt-oss-20b can run on mobile devices, although some experts question the feasibility of this claim [10][45][22] - At least 14 deployment platforms, including Azure and Hugging Face, have already integrated support for these models, indicating strong industry adoption [9][10] Community and Industry Response - While many users celebrate the release, there are concerns regarding the lack of transparency in the training process and data sources, limiting the open-source community's ability to fully leverage the models [9][27][29] - OpenAI's decision to open-source these models is seen as a response to previous criticisms regarding its openness, potentially influencing more developers and companies to adopt these technologies [47]