Sarvam vs ChatGPT And Gemini: Which AI Fits Your Needs

Sarvam AI, a made-in-India artificial intelligence model, is drawing attention in the tech world. Co-founder Pratyush Kumar recently said its multimodal vision-language model, Sarvam Vision, has outperformed global rivals on key benchmarks. The intensifying competition is also fuelling debate on global AI governance - a theme set to be discussed at the NDTV Ind.AI Summit hosted by NDTV on February 18.

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Sarvam AI vs ChatGPT vs Gemini: Which One Fits Your Needs?

Sarvam AI has been designed with a strong focus on Indian languages, but its capabilities extend well beyond localisation. The model performs advanced Optical Character Recognition (OCR), speech recognition and multimodal understanding, enabling it to handle complex workflows involving text, images and audio across diverse use cases.

Global systems developed by OpenAI and Google - such as ChatGPT and Gemini - are widely adopted for coding, reasoning and multimodal applications, supported by large ecosystems and infrastructure.

However, the distinction is increasingly narrowing. Sarvam is positioning itself as an equally capable alternative, combining competitive core AI performance with a significant advantage in Indian language intelligence and local context understanding. In practice, this means users do not necessarily have to choose between global capability and regional relevance - Sarvam aims to deliver both.

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Performance Claims

Sarvam Vision has reported an accuracy score of 84.3% on olmOCR-Bench, an open-source OCR evaluation framework. Its creators say it has surpassed Gemini 3 Pro and ChatGPT on Indian-language benchmarks. However, global models still lead in advanced coding, complex reasoning and deep image understanding.

Sarvam models are also significantly smaller - around 2-3 billion parameters - compared with global systems like Gemini, which are believed to run on far larger compute scales.