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Global Unichip (GUC)

ASIC design for AI accelerators; HBM4 PHY IP

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Where it fits in an AI server rack

ASIC design house affiliated with TSMC (34.84% holder): its 2025 annual report says it assists customers in developing AI accelerator chips with CoWoS and physical-design support, and its 3 nm HBM4 PHY and controller IP became silicon-proven in Q1 2026. In Q2 2026 turnkey revenue rose 188% year on year, and 3 nm and below was 59% of turnkey revenue, mainly from cloud application projects (July 30, 2026).

What the evidence establishes

AI-rack evidence

Disclosed: GUC’s 2025 annual report describes its support for customers’ AI accelerator chips, and its Q2 2026 release attributes most 3 nm turnkey revenue to cloud projects.

An explicit AI-server or AI-rack product, design-in, supply role, program, reference design or partnership, such as a part named for rack-scale AI systems or a product sold for AI data centers. For a rack builder, it means the company’s own AI servers or racks. This does not establish revenue, market share, volumes or future sourcing.

Component roleASIC design for AI accelerators; HBM4 PHY IP
EvidenceDisclosed: GUC’s 2025 annual report describes its support for customers’ AI accelerator chips, and its Q2 2026 release attributes most 3 nm turnkey revenue to cloud projects.
How we knowDisclosed The company’s own filing, release, annual report, product page or investor record describes the AI-server or AI-rack role. Where customers are unnamed, the listing says so.
Primary sourceGlobal Unichip (GUC) — supporting disclosure
Company or official disclosure; vendor claims are attributed to their source.
Checked. This is the research review date, not the source publication or quote time.

Keep in perspective

Customers are unnamed, and cloud projects are not all AI accelerators. GUC designs HBM interface IP on the accelerator die; it does not make HBM stacks.

Specialist business exposure. This describes the breadth or role of the business; it is not an investment rating. An AI-server product, design-in or partnership does not by itself establish material AI-rack revenue, market share, or future returns.

Connections to the assembly

These links explain the technology relationship. The model is illustrative and does not represent an actual manufacturer’s bill of materials.

GPU compute dies

Two reticle-sized logic dies joined into one GPU, built on a leading-edge foundry process. They run the matrix math of training and inference. Custom accelerators designed by or for cloud companies are the main alternative.

Scope of the company links: The compute dies. NVIDIA designs Blackwell and Blackwell Ultra (208 billion transistors on two reticle-limited dies, custom TSMC 4NP) and AMD designs the Instinct MI350 and MI455X; NVIDIA discloses that TSMC fabricates Blackwell. Custom accelerators are the alternative: Broadcom co-develops OpenAI-designed accelerators and racks (its other XPU customers are unnamed), Marvell develops custom AI silicon for unnamed customers, and the design-service houses Alchip (an N3 accelerator for a North American cloud provider, from May 2026) and GUC (AI accelerator design support) disclose programs without naming customers. Intel’s Gaudi 3 is a merchant AI accelerator with no documented rack-scale deployment. Hyperscaler chip designers (Google TPU, AWS Trainium) are not mapped because they do not sell the chips as components. Samsung is named as an NVIDIA wafer foundry but not for Blackwell GPU dies, so it is not mapped here.

Related research

Companies with overlapping sector exposure. Their products and evidence may differ; this is not a list of equivalent investments.

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