In a strategic move aligned with national technology ambitions, Baidu announced two newly developed AI chips, the M100 and the M300, at its annual developer and client event.
The M100, designed by Baidu’s chip subsidiary Kunlunxin Technology, targets inference efficiency for large models using mixture-of-experts techniques, while the M300 is engineered for training very large multimodal models comprising trillions of parameters.
The M100 is slated for release in early 2026 and the M300 in 2027, according to Baidu, which claims they will deliver ‘powerful, low-cost and controllable AI computing power’ to support China’s drive for technological self-sufficiency.
Baidu also revealed plans for clustered architectures such as the Tianchi256 stack in the first half of 2026 and the Tianchi512 in the second half of 2026, intended to boost inference capacity through large-scale interconnects of chips.
This announcement illustrates how China’s tech ecosystem is accelerating efforts to reduce dependence on foreign silicon, particularly amid export controls and geopolitical tensions. Domestically-designed AI processors from Baidu and other firms such as Huawei Technologies, Cambricon Technologies and Biren Technology are increasingly positioned to substitute for western hardware platforms.
From a policy and digital diplomacy perspective, the development raises questions about the global semiconductor supply chain, standards of compute sovereignty and how AI-hardware competition may reshape power dynamics.
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