In 2019, OpenAI released GPT-2 and then completely shut the open-source door. Seven years later, this company did something almost no one anticipated — releasing open-source-weight models.
GPT-OSS 120B officially debuted in April 2026, including gpt-oss-120b and gpt-oss-20b versions, all under Apache 2.0 license, freely downloadable, commercially usable, modifiable, and redistributable. This isn't just OpenAI's first open-source model since GPT-2, but its first real entry into the open-source-weight-model competitive landscape.
On technical architecture, GPT-OSS 120B adopts an improved MoE (Mixture of Experts) architecture. Of the 117B total parameters, only about 39B are activated per forward pass — a design that lets the model run on a single 80GB VRAM GPU with INT4 quantization. In contrast, GLM-5.1 requires 4×H200 to run, DeepSeek V4 requires 8 GPUs. On hardware cost, GPT-OSS 120B has the lowest deployment threshold of the three top open-source models.
Another differentiation highlight is the complete visualization of chain-of-thought (CoT). GPT-OSS 120B offers three reasoning tiers — fast, balanced, deep — letting users observe the model's complete reasoning process in real time, with fine-grained control over reasoning depth. This transparency is unprecedented in open-source models.
On benchmarks, GPT-OSS 120B is on par with GPT-4o on coding and math tasks, and surpasses Llama 3.1 405B with three times its parameter count. But limited by the Apache 2.0 license's 700M MAU threshold clause, its commercial application has certain limits.
OpenAI's entry breaks the open-source competitive landscape previously dominated by Meta, Alibaba, and DeepSeek. GPT-OSS 120B's real significance isn't that it fully surpasses in performance, but that it changes the rules: the ability to deploy top-tier models on a single card has lowered AI inference's hardware threshold from cluster-level to single-card level.