US$300bn pledged to India's data centres; subsidised GPUs reportedly 20% used

01The pledges: more than US$300bn, two-thirds from two Indian groups

Rhodium’s Table 1 lists twelve commitments, from Reliance’s US$110bn over 2026–2032 and the Adani Group’s US$100bn through a joint venture over 2026–2035, to US$1bn from Airtel’s Nextra.¹ The government’s own framing is narrower: a PIB backgrounder of 14 September said “investments of nearly USD 70 billion are already underway”, with “an additional USD 90 billion in announced projects”, and put installed data-centre capacity at 1.57 GW in August 2026, projected to reach nearly 8 GW by 2030.³ At the India AI Impact Summit in February, PIB recorded Reliance’s pledge as “USD 110 billion over seven years towards AI-focused infrastructure” and Adani’s as “USD 100 billion by 2035”.⁴

Rhodium’s account of why the money comes covers cost, power and tax. Mumbai ranks as the second-cheapest major hub in the world to build a data centre, after Shanghai; India installed a record 50 GW of renewable capacity in 2025; and the Union Budget added a 20-year tax holiday for foreign cloud providers. It also notes that India produces 20% of the world’s data but hosts under 3% of global data-centre capacity, and that a typical project can need 30–40 separate approvals.¹

02The GPUs: 38,000 for five months, then 45,000

The IndiaAI Mission, approved in March 2024 with ₹10,371.92 crore over five years, began with a target of 10,000 GPUs.⁶ MeitY said on 30 May 2025 that the common compute capacity had crossed 34,000.⁵ From October 2025 PIB put it at 38,000, available at ₹65 an hour, which it called on 10 February “nearly one third of the global average cost”.⁶⁷ On 17 February, at the AI Impact Summit, the IT minister, Ashwini Vaishnaw, said India would add 20,000 GPUs “in the coming weeks” beyond the existing 38,000.⁸ On 25 March PIB still gave “more than 38 thousand”.⁹ A PIB factsheet of 13 August gave “45,000+ Graphics Processing Units (GPUs), as of June 2026”.¹⁰

Both numbers are the government’s, at different dates: 38,000 in statements from October 2025 to March 2026, and 45,000+ as of June 2026 in the August factsheet. The 38,000 plus the promised 20,000 would be 58,000; the government has not said, in any document we found, how many of the 20,000 had arrived by June. We found no dated official target beyond that February promise.

03The use: one GPU in five, reportedly

Rhodium wrote that “nearly 80% of its GPUs reportedly sit unused, despite availability at prices less than 40% below the market rate”. The report names no source for the 80% figure.¹ Its reasons are on the demand side: “only a handful of India’s AI startups actually train models and therefore need dedicated GPU clusters”, and Indian AI startups raised US$1.3bn last year, which it puts at 0.6% of private equity and venture money invested in the world. It also wrote that enterprise and edge data centres used only by Indian entities are “less than 13%” of India’s operational capacity, against roughly 60% leased out by hyperscalers.¹

Where the capacity goes instead is also in Rhodium’s account. Yotta’s chief executive “estimates that nearly 80% of revenue already comes from foreign clients”, and the company “plans to allocate half of its $7 billion worth of NVIDIA GPUs purchases this year” to NVIDIA’s DGX Cloud Lepton marketplace under a US$1bn, four-year agreement.¹ Rhodium’s reading is that India’s data centres “will primarily be used to scale global cloud ecosystems rather than serve the domestic market”. The government’s reading, in the same months, is of “affordable high-performance computing” that is “lowering entry barriers for Indian researchers, start-ups and innovators”.¹¹⁰ We report both; the hours and the GPU count above are the only measured numbers either side has published.

04What a buyer can do: apply for the subsidised hours

The capacity is rented through the IndiaAI Compute Portal. Startups and MSMEs qualify with DPIIT recognition, experience in AI or machine learning, and annual revenue of ₹50 lakh or funding of ₹1 crore; researchers with an h-index of 5 or more, AI publications in journals with an impact factor above 2.5, or 150+ citations; early-stage startups with four years of AI experience and a letter from the IndiaAI CEO or a joint-secretary-rank officer; and students, IndiaAI fellows and government entities on their own criteria.¹¹