Open models have real benefits. Do they outweigh the risks?

MIT Technology Review Explains: Let our writers untangle the complex, messy world of science and technology to help you understand what’s coming next. You can read more from the series here. Late last month, Anthropic released a report arguing that the model GLM-5.3 poses a major cyberattack risk.…

Résumé

Open vs closed models

The article distinguishes between open models and closed models in artificial intelligence (AI).

Closed models, like those powering ChatGPT or Claude, can only be accessed through a website, app, or API, meaning users interact with them remotely without seeing their internal workings.

Open models, such as GLM-5.3, are freely downloadable, allowing users to run them on their own hardware, modify their code, or retrain them.

Open models are often called open-weight models because their internal structure, encoded as numerical values called model weights, is publicly available.

While closed models currently outperform open ones—holding the top eight positions on the Artificial Analysis LLM leaderboard—open models offer unique advantages.

Researchers rely on them to study AI systems in depth, as they can observe the model's chain of thought (the step-by-step reasoning process) and experiment with combining or fine-tuning them.

Businesses may prefer open models for cost savings and security, as they can process sensitive data locally without relying on external providers.