Rohan Paul on X: "Per The Information, Zhipu AI is also (after DeepSeek) exploring a custom ASIC after GLM-5.2 usage reportedly jumped 27x in one week. A custom ASIC removes flexibility, but it can cut power draw and per-token cost. Nvidia GPUs are strong general-purpose machines, but inference http
Quick Answer
Zhipu AI is exploring a custom ASIC following a 27x increase in GLM-5.2 usage, aiming to reduce power draw and costs.
Quick Take
Zhipu AI is exploring a custom ASIC following a 27x increase in GLM-5.2 usage, aiming to reduce power draw and costs. While Nvidia GPUs excel in general-purpose tasks, dedicated silicon may enhance performance for specific models. The project, which may take over two years, reflects a broader trend among Chinese AI firms to integrate software and hardware more closely.
Key Points
- GLM-5.2 usage surged 27x in one week, prompting Zhipu AI's ASIC exploration.
- Custom ASICs can reduce power draw and per-token costs but lack flexibility.
- Nvidia GPUs are strong general-purpose machines but may not be optimal for all tasks.
- DeepSeek is also developing an inference chip to reduce reliance on Nvidia and Huawei.
- The project may take more than two years and lacks a chosen partner.
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~1 min readPer The Information, Zhipu AI is also (after DeepSeek) exploring a custom ASIC after GLM-5.2 usage reportedly jumped 27x in one week. A custom ASIC removes flexibility, but it can cut power draw and per-token cost. Nvidia GPUs are strong general-purpose machines, but inference at scale has different economics. A fixed model can run better on silicon designed around its own repeated operations. Zhipu has not chosen a partner, and the project may take more than 2 years. The pattern is now bigger than one Chinese lab or one model launch. Chinese AI companies are trying to make software, hardware, and deployment less separable.
— Originally published at x.com
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