文心 5.5 Flash
Baidu ERNIE's next-generation foundation model focused on inference efficiency, with an open-sourced Base version.
Baidu released ERNIE 5.5 Flash Preview, built on a new architecture optimized for efficient inference, with 280B total parameters and 14B active per token, a 1M-token context window, and generation speed above 200 tokens/sec. The model is now live on Arena for testing, with Baidu claiming competitive results on Terminal-Bench and AutomationBench; open weights are slated for release by November 25.
Baidu ERNIE disclosed its recursive self-improvement (RSI) system ERNIE Evolve for the first time, which uses a multi-agent dual-loop design to autonomously propose research directions, modify code and validate results, achieving publicly verified SOTA on three metrics across NanoChat AutoResearch and NanoGPT Speedrun. The system has been deployed in real inference optimization for ERNIE 5.5 Flash, lifting generation speed to 623.6% of baseline in low-latency scenarios on Kunlunxin P800 and raising deterministic inference throughput to 133%. Baidu open-sourced ERNIE 5.5 Flash Base on November 5, with a new model expected soon.