The Cheapest AI in the World Is Indian. It Is Also the Weakest

Ask your bank's chatbot why a payment failed. Ask a homework app to explain photosynthesis to a Class 8 student. Something answers in a second, in decent English.

Almost none of that something was built here. Of all the AI work Indian developers sent out between January and July through OpenRouter, the service that routes requests to hundreds of models at once, 94% went to machines built in America or China, according to figures published by Bloomberg Businessweek.

Artificial Analysis, a benchmarking firm whose scoreboard the AI companies quote at each other, runs every major model through the same nine tests. It tracks 610 of them. Of the 257 still on sale, two were built in India, both by the same Bengaluru company, Sarvam.  India is Ninth Out of Eleven

India's best model is called Sarvam 105B. It scores 11.9 out of 100 on that scoreboard, according to Artificial Analysis data read on August 20, 2026. Anthropic's Claude Opus 5, the world's best, scores 63.1. China's best, Kimi K3, scores 59.7.

Line up the countries by the strongest model each has, and India comes ninth of the 11 that have built anything at all, behind South Korea, Singapore, France, Canada, Spain and the United Arab Emirates.

One caveat travels with India's number. Artificial Analysis marks both Sarvam scores as estimates rather than full test runs, which it does when a model has not been through the whole suite. The ranking holds; the exact figure is not a measured one.  Two Years Behind, in Plain Terms

Points out of 100 mean little on their own. Time is easier to feel. The first AI model ever to score higher than 11.9 was o1-preview, which OpenAI released on September 12, 2024, according to the same scoreboard. India's best model today is roughly where the world's best stood two years ago. Of the 257 models a developer anywhere can buy this month, 171 score above it.

The gap is not closing quickly, because India is barely in the queue. Since January, the United States has put out 113 new models and China 91. India has put out two.

Nor is the frontier the only thing ahead of it. gpt-oss-120b, a model OpenAI released free for anyone to download and run on their own machines, scores 24.1. That is more than double Sarvam 105B.  What India Did Get Right

Sarvam is close to the cheapest thing on the board. A batch of work that costs $10 to run through Claude Opus 5 costs about seven cents through Sarvam 105B, a 135th of the price. And Sarvam gives its models away free to download and run, which neither OpenAI nor Anthropic allows with their strongest models.

That is the opening China took. Chinese labs went cheap and open, and in June their models overtook American ones on OpenRouter. More than 60% of the work routed through it last month went to Chinese models, according to figures published by Bloomberg Businessweek.

It has not worked that way at home.  Ninety-Four Out of Every Hundred

That traffic is not small. India pushed 9 trillion tokens through OpenRouter over those seven months. A token is the word-fragment an AI reads and writes. That makes India the 10th-largest market in the world. And 51% went to American models, 43% to Chinese ones.

The six squares left over cover every other country on earth, India's two models among them. It is a remainder rather than a measured Indian share, and still the closest thing anyone has to a figure for how much of India's AI work runs on Indian AI.  The Test Nobody Sets in Tamil

The nine tests measure coding, scientific reasoning, general knowledge and how well a model works on its own. Not one measures an Indian language. Nothing in the score says whether a model can take a complaint in Bhojpuri, read a land record in Marathi or answer a pension query in Tamil. That is the problem Sarvam was set up to solve, and the one a global leaderboard cannot judge.  Not Everyone Thinks This is a Problem

India's most quoted technologist says it should not be. At the NCAER India Policy Forum in New Delhi on August 6, 2026, Infosys co-founder Nandan Nilekani argued the country should stop chasing the frontier. "The Western focus on AI is on infrastructure like larger models, more chips, more data centres. But infrastructure eventually gets commoditised," he said, as reported by the news agency IANS. "The value shifts to the application layer, and India can become the AI use-case capital of the world."

The numbers give him something to stand on. Stanford University's AI Index found that 58% of employees worldwide used AI at work regularly in 2025, but that in India, China, Nigeria, the UAE, Egypt and Saudi Arabia the share passed 80%. India is among the heaviest users of a technology it does not build.

The same report found India registered the sharpest rise in concern about AI of any country surveyed between 2024 and 2025, up 14 percentage points against two points of extra excitement. Being the use-case capital also means being the most exposed to decisions taken in San Francisco and Hangzhou.

The government's answer so far has been silicon. The IndiaAI Mission has been buying GPUs, the chips these models are trained on, and renting them to startups, researchers and universities at subsidised rates. Beijing is preparing to spend about 2 trillion yuan, or $295 billion, on data centres over the next five years, according to Bloomberg.

Chips are necessary. They are not the same as a model.

Of the two gaps in this story, the second is the one India can close first. A country can change what it buys faster than it can change what it builds. Since January, it has added two models, and its share of its own AI work has not moved.