- Sarvam AI says its Sarvam Vision model outperforms Gemini and ChatGPT on key OCR benchmarks
- The startup focuses on India’s 22 official languages.
- Its “sovereign AI” approach aims to create technology tailored specifically to India’s needs.
ChatGPT, Gemini, and other AI chatbots are often very good at reading English and many other languages, but while they can interpret Hindi, they start to falter when faced with more complex scripts or regional nuances among Indian languages.
Now, a Bengaluru startup called Sarvam AI is moving forward with models that it claims can surpass its global rivals when it comes to optical character recognition (OCR) and multilingual speech, particularly when it comes to the languages of the subcontinent.
In Indian languages, Sarvam Vision is the best model by far, supporting all 22 Indian languages programmed pic.twitter.com/nM4Ujz0wvPFebruary 5, 2026
Sarvam Vision and Bulbul V3 models are built keeping in mind the linguistic complexity of India. Sarvam Vision can interpret complex tables, understand graphics, recognize text in real-world scenes and generate subtitles, while Bulbul V3 handles the text-to-speech system. They support all 22 official languages of India.
With 35 voices, Bulbul can always sound like a local. As many multilingual users know, the discomfort of hearing their language pronounced as if it were a distant cousin of English can make someone reluctant to try the technology. A well-trained text-to-speech model that captures pace and tone more accurately can make people more comfortable using it.
And while OCR may not seem glamorous, it quietly powers everything from scanning a document with your phone, uploading a PDF, or digitizing an old record. Garbled characters, misread names, and lack of context can be a real problem. Sarvam says it will help small business owners and government offices convert records into searchable files more quickly and accurately than would otherwise be possible.
Sovereign AI
Sarvam AI calls itself a sovereign AI builder. The idea is to differentiate itself from foreign platforms. With AI models spreading across government, business and education, questions about who builds them and what data they understand are very important. Sarvam wants to have tools adapted to India.
The emergence of Sarvam also drives a broader conversation about where innovation originates. The rise of AI has often been framed as a race between a few dominant players. However, advances increasingly come from teams focused on solving specific problems. Sarvam appears to have identified a gap in high-quality, language-rich speech and OCR systems for Indian scripts.
Of course, benchmarks are snapshots, not guarantees of performance, especially in the real world. The proof of Sarvam’s impact will be in adoption. Additionally, if Sarvam’s claims hold up, larger AI companies will feel pressure to improve their own support for more languages and scripts.
At its best, Sarvam AI’s story goes beyond beating Gemini or ChatGPT on a leaderboard and becomes a way to show that technology reflects the people who use it. If AI is going to shape the next decade of digital life, you will need to speak many languages fluently and read more than just plain English texts.
Sarvam is betting that attention to detail and cultural specificity can compete with grand scale. For millions of users who have felt neglected by mainstream AI tools, that bet may seem safer.
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