From Importer to Innovator: Building India’s GPU Roadmap for the AI Era
India is at the threshold of the AI age, yet the engines that power AI — GPUs — remain conspicuously absent from its industrial base. Despite grand ambitions under the India Semiconductor Mission and the promising rollout of the IndiaAI program, India has positioned itself more as a consumer of compute, not its creator. As the global race for artificial intelligence tightens, this absence of indigenous GPU capabilities could leave India strategically handicapped. If compute is the new oil, then India risks becoming the customer at the pump, not the producer.
To understand where we are and where we must go, one must first grasp what GPUs are and why they matter. GPUs, or Graphics Processing Units, are no longer just about rendering high-end visuals in games. They are the computational workhorses of modern AI systems, deep learning models, scientific simulations, and real-time analytics. Unlike general-purpose CPUs, GPUs handle thousands of operations in parallel, making them essential for training large language models (LLMs), powering data centers, and enabling breakthroughs in drug discovery, weather modeling, and autonomous systems.
The global GPU landscape is brutally consolidated. NVIDIA commands over 90% of the AI GPU market, with AMD and Intel trailing distantly. Fabrication is outsourced to TSMC (Taiwan) and, to a limited extent, Samsung. Nations like the United States, China, and even the UAE are building or hoarding compute capacity as a national strategic asset. The US alone has access to over a million GPUs, and China is attempting to match that despite export controls. India, by contrast, has secured bids for approximately 18,000 GPUs under the IndiaAI compute tender, most of them imported, with no roadmap for domestic design or fabrication.
That brings us to India’s semiconductor policy. The India Semiconductor Mission, with its Rs 76,000 crore outlay, is a historic initiative. It rightly prioritizes building fabs, ATMP facilities, and chip design capabilities. The DLI (Design Linked Incentive) scheme has shortlisted over 20 design startups. However, the elephant in the room is that not a single initiative targets GPU development. Most startups are working on microcontrollers, RISC-V based CPUs, and application-specific designs for automotive or IoT. The GPU space — far more capital-intensive and IP-heavy — remains untouched.
So what should India do? First, we need to articulate a GPU Roadmap as a national mission — just as we did with ISRO’s space program or BARC’s nuclear research. This roadmap should rest on five foundational pillars.
1. GPU Design Ecosystem: India must incubate startups or public-private consortiums that aim to design AI-specific GPUs. Collaborations with IITs, DRDO, and global chip IP providers should be fast-tracked. We need a “Bharat GPU” program with targeted funding, open IP cores, and clear commercialisation pathways.
2. Build 5–7nm Fab Capability: Mature-node fabs at 28nm will never be able to fabricate modern AI chips. India must strike strategic partnerships with TSMC, Samsung, or Intel Foundry Services to co-build advanced fabs. Without domestic access to sub-10nm lithography, GPU dreams will remain on paper.
3. National GPU Compute Grid: Instead of fragmented infra, build a sovereign AI cloud backed by Indian data center firms. This compute grid can offer subsidised access to academia, startups, and government missions. UAE’s G42 or Europe’s GAIA-X are good templates.
4. Trusted Supply Chains: Invest in OSAT (outsourced semiconductor assembly and testing) units focused on GPU packaging. Encourage local production of memory, interconnects, and boards that integrate with GPU systems.
5. Talent & Tooling: India must train thousands of engineers in GPU architecture, parallel computing, and EDA tools. Provide public access to simulation frameworks, NVIDIA CUDA, and alternative AI toolkits.
But here lies the mismatch. Current policy structures treat all semiconductors with a broad brush, missing the nuanced reality that GPUs demand a unique ecosystem. Building a microcontroller or an IoT sensor does not require the same kind of lithography, thermal management, memory bandwidth, or software stack that a GPU does. Yet, the DLI scheme today offers identical incentives to a firm building a low-end automotive chip and one that aspires to build a high-end AI processor. This one-size-fits-all approach risks diverting resources away from areas where India truly needs to build strategic depth.
Furthermore, while MEITY has commendably driven momentum on chip design startups, there is no vertical integration between this effort and India’s needs in sectors like national defense, space research, medical diagnostics, and sovereign AI infrastructure — all of which are heavily dependent on AI compute. There is no nodal agency or mission directorate tasked with thinking exclusively about GPU-class infrastructure and capability development. As a result, India is investing in building roads but not ensuring that high-performance vehicles can run on them.
Even the IndiaAI mission, as transformative as it is in making GPU compute affordable and accessible, is essentially a rental model. It democratizes access to imported GPUs but does not alter the global power structure. NVIDIA remains the gatekeeper. The moment export controls tighten or geopolitical alignments shift, India’s AI dreams could be choked at source.
The current strategy, in its present form, is focused more on import facilitation than on innovation leadership. It is solving for cost, not sovereignty. Accessibility without autonomy is short-lived empowerment.
We advise a mid-course correction. Create a vertical within ISM or IndiaAI called the “GPU Sovereignty Mission”. Allocate at least 25% of DLI funds exclusively to high-performance compute design. Launch a national “GPU Design Challenge” across academia and industry. Incentivize Indian hyperscalers to invest not just in hosting GPU racks, but in R&D partnerships for next-gen chips.
India’s moment is now. With AI exploding and geopolitics reshaping supply chains, compute is no longer just an enabler — it is power. If India wants to be more than a backend to Western models, it must claim its space in the GPU age.
