Going by , this model must have required a few thousand crores and yet hardly offered any gains. OpenAI announced in April that they will be discontinuing this model for developers, which comes down to its unreasonably high serving cost. Most industry players, including OpenAI and Google, have not obtained their recent performance gains by training a bigger or different language model. The Indian government should be taking notes and instead invest in alternative approaches that market-leading companies may not have focused on due to intense competition and investor pressure.
While the Ghibli-style image trend has helped AI companies get some traction lately, they have been burning enormous cash with no return on investment in sight. Take OpenAI as an example. Since 2023, the company has raised a new funding round every 12 months. In 2023, they over $10 billion followed by $10.6 billion in 2024, and now $40 billion in 2025. That is over $60 billion of investor money in three years. Meta is planning to allocate a good chunk of its projected $65 billion in 2025 capital expenditures to AI, and so is . Does the Indian government have the vision and budget to potentially invest thousands of crores on an Indian LLM, or are we just giving token money to build a system that would never really be usable?
It is not the capital that is holding back India in this race. Look at Krutrim, an LLM released by Ola. Despite all the funding, they are yet to produce a compared to those developed global competitors. The fundamental requirements to come up with groundbreaking technology are exceptional talent, research calibre, visionary scientific leadership, minimal administrative hurdles, and then and only then, capital to make sure that money problems of running such an effort can be solved.
India still needs to retain its top talent—the ones who go abroad and lead AI efforts at OpenAI, Google, Meta—reduce administrative hurdles for businesses, and foster a high-quality research culture in academia, which is the foundation of such innovation. Leave it to the private markets and investors to figure out their way from there on.
While fears that China or the US may be left with sole access to AI sound alarming, we need to remember that most technologies around the world have been built on the back of open-sourcing, which is releasing software code for free public use. This has continued with LLMs, where players like Microsoft, Mistral AI, Meta, DeepSeek, Alibaba, and others have and continue to release their LLMs for free. These models can be downloaded easily, do not have a backdoor to any foreign governments, and are within 5-10 per cent of the performance range of commercial models. If Indian companies need to research AI, they can easily start with one of these open-source models and build their own using them. There is no need to fund the creation of a new language model and reinvent the wheel.
Let’s assume that the government goes ahead and keeps funding the development of an LLM. Then who takes care of the recurring talent and maintenance costs, which are per cent of a company’s budget worth thousands of crores? Why should a user prefer this model over OpenAI, Google, xAI or DeepSeek? Will this Indian model perform equally well in programming, science, and mathematics as the rest of the models? If a private company like Sarvam AI has been tasked with developing the model, why not just have private investors fund the project? The government should be easing administrative hurdles, not betting on private markets.
It’s not that we shouldn’t be pursuing AI or funding its growth. There are many ways in which state funding could be of use. The digitisation of instructional datasets of local languages would help global and local AI companies make their LLMs understand Indian languages better. Curated knowledge bases and documents that can help debias state-of-the-art AI models on Indian history, narratives, and religions can educate global and local audiences on Indian issues. There can be various applications of LLMs in governance.
For now, we need to be aware that there is no clear path for a return on investment from LLMs. And so far there are no signs that we are anywhere close to even general intelligence. Let us have the private markets play out this bet. There is no dearth of areas where taxpayers’ money can be better spent.
(Edited by Aamaan Alam Khan)
