What happened
Indian AI lab Sarvam released five open-source models. The suite includes 30-billion and 105-billion parameter large language models. Sarvam also shipped specialised text-to-speech, speech-to-text, and document-parsing vision models. These tools prioritise Indian languages and local data sovereignty. The release provides developers with high-parameter alternatives to proprietary systems. This expansion follows Adani Group’s 17 February commitment of 100 billion dollars to Indian AI data centres.
Why it matters
CTOs and procurement teams gain high-performance, open-source alternatives to proprietary APIs. Local hosting reduces data residency risks and cuts inference costs because these models run on domestic infrastructure. This release validates the 100 billion dollar data centre commitment from Adani Group and Microsoft’s 17.5 billion dollar regional investment. Therefore, Indian founders can build sovereign AI stacks without Western licence constraints. This follows the pattern of specialised model releases seen with Arcee AI’s Trinity launch in January.
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