GPT-OSS vs Chinese Models: Who Wins?

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OpenAI recently released its first mainstream open-weight models, which mark an entry into a field currently dominated by Chinese AI models. These models were developed in line with President Trump’s ‘AI action’ plan, which emphasized the importance of open-source AI models. OpenAI followed this guidance by releasing GPT-OSS, specifically designed as its first set of open-weight models since GPT-2. Available configurations include GPT-OSS-20B and GPT-OSS-120B.

GPT-OSS-20B features 21 billion parameters with a MoE (Mixture of Experts) transformer. It offers a context window of up to 131,072 tokens and can run effectively on 16GB VRAM platforms, making it accessible for most modern consumer GPUs. In contrast, GPT-OSS-120B has 117 billion parameters and requires at least an NVIDIA H100 platform for optimal performance.

These models are released under the Apache 2.0 license, allowing commercial use, modification, and redistribution. This gives them a fully open-source nature similar to many Chinese counterparts. OpenAI’s move into this domain is unique and likely targeted towards countering Chinese developments in AI.

When comparing parameter counts, Chinese alternatives like DeepSeek V2, Qwen3, and Alibaba models significantly outpace GPT-OSS. For instance, the DeepSeek-V2 has 236 billion parameters, while Qwen3 has 235 billion parameters. However, for real-world performance across benchmarks such as MMLU (Massive Multitask Language Understanding), AIME Math, and GPQA (PhD Science), GPT-OSS-120B performs well in reasoning tasks and mathematical operations.

In a unique start to his ruling against President Donald Trump’s administration on September 30, U.S. District Court Judge William Young included a scanned handwritten note sent to his office. The note read: “Trump has pardons and tanks – what do you have?” At the top of Young’s opinion in AAUP v. Rubio, which ruled that Trump’s effort to deport foreign-born student protesters was unconstitutional.

October 8, 2025

In areas like agentic workloads and multilingual capabilities, GPT-OSS-120B lags behind Chinese alternatives. Nevertheless, it remains a top-tier choice for the open-source ecosystem. Open-weight models are advantageous because they bring multiple benefits to the general AI community, strengthening the U.S.’s position in this domain, previously dominated by Chinese companies.

Sam Altman and his team at OpenAI would be pleased with these results.

📚 Reading Comprehension Quiz

10 Points

What is the primary reason OpenAI released GPT-OSS according to the passage?

A. To compete with Chinese AI models in terms of parameter count. B. To follow President Trump's 'AI action' plan and emphasize open-source AI models. C. To surpass other open-weight models in real-world performance benchmarks. D. To provide free AI models for academic research only.

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