ByteDance's Doubao Large Model 2.2, which was initially slated for an August release, has been delayed. Internally, the decision was made to allocate extra time for both pre-training and post-training phases. This additional time will be used to bolster the model's programming prowess, tool invocation efficiency, and Agent capabilities. The team has opted for a lengthier development cycle, believing it will yield more substantial enhancements. Version 2.2 stands as a pivotal upgrade between two generations of models, striking a balance. It avoids waiting for the next-generation ultra-large model to be finalized before tackling programming challenges, and it also eschews the simplistic iterative approach of the past. The Seed team has set an ambitious goal: to elevate the model's programming capabilities to the top tier by 2026. ByteDance envisions that, by year's end, the model will wield industry influence comparable to that of Zhipu's GLM-5.2 and Kimi-K3. Zhang Yiming has made it clear that the company will eschew AI distillation techniques in its quest to improve models. Meanwhile, Liang Rubo has affirmed ByteDance's commitment to self-developed large language models, emphasizing a focus on foundational skills, accepting short-term setbacks, and pursuing long-term optimization.