AI Glossary

What is Application-Specific Integrated Circuit (ASIC)?

Insta's plain English

A chip hard-wired for one job. In AI, custom ASICs can run specific workloads cheaper and faster than off-the-shelf GPUs.

An ASIC is a chip custom-built for one specific job. In AI, ASICs are designed to run particular AI workloads more efficiently than general-purpose GPUs.

The full picture

Unlike a flexible GPU that can run almost any AI task, an ASIC is etched for a narrow purpose — and that focus makes it faster and more power-efficient for that job. Google’s TPU is a famous AI ASIC.

ASICs matter because they offer a path around Nvidia’s dominance and rising GPU costs. Companies like ByteDance are commissioning custom AI ASICs, and chipmakers such as Qualcomm, Broadcom, and Marvell are competing to build them. The trade-off: ASICs are expensive to design and inflexible once made, so they suit large, stable, high-volume workloads.

📌 Real business example

A large platform with a single dominant AI workload commissions custom ASICs to cut its per-query cost at scale — a bet that only pays off because its volume is huge and predictable.

How different roles use this

Technical lead

Weighs custom ASICs against flexible GPUs based on workload stability and volume.

Executive

Sees the rise of custom AI ASICs as a force that could loosen Nvidia’s grip and lower long-term costs.

Procurement lead

Factors chip diversity (GPU vs ASIC supply) into vendor and capacity planning.

Common questions

Q: How is an ASIC different from a GPU?

A GPU is general-purpose and runs many AI tasks. An ASIC is custom-built for one task — faster and more efficient for that job, but inflexible and costly to design.

Q: Should my business care about ASICs?

Indirectly. You won’t design one, but the spread of AI ASICs increases competition and can lower the cost of the AI services you buy.