OpenAI Developing 'Garlic': A Specialized Model That Achieves Flagship Performance at Scale

OpenAI is reportedly developing a new large language model (LLM) codenamed 'Garlic,' marking a strategic pivot toward specialized high-value industries and increased scaling efficiency for its core consumer platform. This new model is designed to overcome structural issues encountered in preceding versions, aiming to infuse the knowledge and reasoning power of larger models into a much smaller, more efficient architecture.

The 'Garlic' project builds upon lessons learned from an earlier internal model, Shallotpeat, with a focus on resolving key technical bottlenecks during the pretraining phase. Chief Research Officer Mark Chen stated that the team has achieved a breakthrough in efficiency, effectively managing to fit the knowledge base typically requiring massive parameters into a smaller, faster model. This advancement is crucial for OpenAI, as it offers a more cost-effective and agile path to delivering advanced capabilities without inflating training and inference costs.

Internal evaluations suggest 'Garlic' is already performing strongly against current frontier models. Reports indicate that 'Garlic' is achieving impressive results compared to Google’s Gemini 3 and Anthropic’s Claude Opus 4.5, particularly in high-value use cases such as coding and advanced reasoning tasks. This specialized intelligence signals OpenAI's move into focused applications like biomedicine and healthcare. The model is expected to undergo post-training, rigorous safety testing, and could see a public debut as GPT-5.2 or GPT-5.5 by early 2026. This push for efficiency directly supports CEO Sam Altman’s internal focus on urgently augmenting ChatGPT’s responsiveness and personalization features to improve the user experience globally.