Partnership · AI & Deep Tech
Cerebras partners with G42 to build India's largest AI supercomputer
By Startup Enthusiast ·
- Date
- Company
- Cerebras Systems
- What it does
- Builds massive AI processors
- Kind
- Partnership
- Amount
- $5.55 billion
- Founded
- 2015
- Sector
- AI & Deep Tech
What they do
Cerebras builds giant chips using entire silicon wafers for high-speed AI training
What happened
India and UAE executed a partnership to deploy an 8-exaflop cluster in India
Why it matters
The project brings sovereign compute power to Indian startups and researchers onshore
The details
- UAE President gifted a Cerebras chip to PM Modi marking the Condor Galaxy India partnership.
- The deal involves deploying 64 Cerebras CS-3 systems to build one of India's largest AI clusters.
- The partnership signals growing importance of AI infrastructure in India-UAE cooperation.
- The project aligns with domestic ambitions by bringing sovereign AI compute onshore.
- It reduces dependence on foreign cloud infrastructure for startups and researchers.
- PM Modi and UAE President announced the project during a visit in January 2026.
- A term sheet was signed between G42 and C-DAC at the India AI Impact Summit.
- G42 will handle installation, deployment, operations, and maintenance of the system.
The bigger picture
- The project addresses data sovereignty by hosting infrastructure and data within India.
- It provides affordable access to frontier-scale computing power for local entities.
- The capacity is almost 19X compared to India's two flagship AI supercomputers.
- It offers greater control over data residency, security, and national control.
About the business
- Cerebras builds a single massive processor called the Wafer-Scale Engine (WSE).
- The company uses an entire silicon wafer instead of individual chips.
- They solve integration challenges by adding spare cores to reroute around flaws.
- Cerebras went from selling hardware boxes to building giant cloud supercomputers.
- The technology claims up to 20X faster AI training and inference speeds.
- It trains models with up to 24 trillion parameters without code splitting.
- The WSE-3 features 44 GB of on-chip SRAM for rapid data movement.
- The chip houses over 4 trillion transistors on a single piece of silicon.
- It claims aggregate bandwidth of 214 petabits per second.
What happens next
- The facility will help train large AI models much faster.
- It will offer affordable access for research and commercial use.
- The project will likely be used for drug discovery and disaster management.
- It aims to simulate smart energy grids and foster research.
The deal
- Type
- partnership
Founders
- Andrew Feldman, CEO
- Gary Lauterbach, Co-founder
- Michael James, Co-founder
- Sean Lie, Co-founder
- Jean-Philippe Fricker, Co-founder
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