The global AI race has long been a duel between Silicon Valley’s brute force and China’s algorithmic efficiency. But as of February 18, 2026, a new contender has officially entered the heavyweight ring. Bengaluru-based startup Sarvam AI has just unveiled its most ambitious lineup yet, the Sarvam-30B and Sarvam-105B models, aimed squarely at providing a “Sovereign AI” for 1.4 billion people.
While the world was busy debating GPT-5 or DeepSeek’s cost-efficiency, Sarvam AI quietly achieved something remarkable. It didn’t just build a “wrapper” around foreign tech; it built foundational models from scratch that have already started beating the likes of ChatGPT and DeepSeek in specific, high-value benchmarks.
How Sarvam Beat the Giants
The headline-grabbing claim that “Sarvam AI beat ChatGPT” isn’t just marketing hype; it is grounded in the grueling world of Optical Character Recognition (OCR) and document intelligence. On February 5, 2026, Sarvam Vision topped the olmOCR-Bench, an industry standard for reading scanned documents, complex layouts, and handwritten text.
| Model | Accuracy (olmOCR-Bench) | Specialized Context |
| Sarvam Vision | 84.3% | Indian Scripts & Mixed Layouts |
| OpenAI ChatGPT (GPT-4o) | ~78% | General English-first |
| Google Gemini 3 Pro | ~80% | Multilingual General |
| DeepSeek OCR v2 | ~81% | Chinese/English Optimized |
Export to Sheets
Why does this matter? For the “Indian ChatGPT” to be useful, it must understand a handwritten bank form in Marathi, a technical table in a government PDF, or a “Hinglish” electricity bill. Sarvam’s models achieved a staggering 93.28% accuracy on OmniDocBench v1.5, proving that when it comes to the messy, multilingual reality of Indian paperwork, the global giants are actually the underdogs.
The Technical Secret: Solving the “Token Tax”
To understand Sarvam’s edge, we have to look at Tokenization. In AI, words are broken into “tokens.” Historically, Indian languages suffered from a “Token Tax.” A single word in Hindi or Tamil could take 4 to 8 tokens to process, whereas an English word took only 1 or 2. This made foreign models slower, more expensive, and less accurate for Indians.
Sarvam AI engineered a breakthrough custom tokenizer. By training on a massive 16-trillion-token corpus (with 2 trillion high-quality Indic tokens), they achieved a fertility rate of 1.4 to 2.1. This means their AI “speaks” Indian languages as naturally and efficiently as GPT-4 speaks English.
Furthermore, their new 105B parameter model uses a Mixture-of-Experts (MoE) architecture. Instead of firing up all 105 billion parameters for every query, it activates only the specific “experts” needed. This keeps the inference 4-6x faster than traditional models, allowing it to run smoothly even on basic feature phones, a capability demonstrated today through their “Vikram” chatbot.
Hardware and Sovereignty: The 40,000 GPU Powerhouse
No AI can survive on code alone; it needs the “iron.” One of the biggest reasons Sarvam AI is being taken seriously is its deep integration with the IndiaAI Mission. Supported by the Government of India, Sarvam has secured access to over 40,000 GPUs, including the latest NVIDIA H100s via Yotta’s Shakti cluster.
This is part of a larger strategic shift. During the 2026 Union Budget, India announced a tax holiday until 2047 for data centers. The goal is clear: India wants to move the “compute power” of the world onto its own soil. By building its models on this sovereign infrastructure, Sarvam ensures that Indian data never has to leave the country to be “understood” by a server in Oregon or Shanghai.
Beyond the Screen: Sarvam Kaze and Voice-First AI
The most visible sign of Sarvam’s ambition appeared yesterday, February 17, 2026, at the India AI Impact Summit. Prime Minister Narendra Modi was spotted testing Sarvam Kaze, India’s first indigenous AI-powered smart glasses.+1
Unlike Meta’s Ray-Bans, which are heavily optimized for Western contexts, the Kaze is built for the Indian street. It doesn’t just “see”; it translates real-time street signs in 22 official languages and responds to voice commands in regional accents.
This points to Sarvam’s true strategy. They aren’t trying to build a better “writing assistant” for corporate emails. They are building a Voice-First AI that helps a farmer in Punjab or a small shopkeeper in Kerala interact with the digital world without ever needing to type a single word in English.
Can it Truly Become the “New ChatGPT”?
Is Sarvam AI ready to replace ChatGPT for everyone? The honest answer is: Not yet, but it’s not trying to.
ChatGPT remains the “Jack of All Trades.” If you want to debug complex Python code or write a philosophical essay on Kant, OpenAI still holds the edge in general reasoning. However, Sarvam AI is the “Master of India.” It is optimized for:
- Hyper-local accuracy: Navigating the nuances of 22 languages and 100+ dialects.
- Cost-efficiency: Providing API services at a fraction of the cost of GPT-4.
- Document Intelligence: Processing the billions of physical documents that fuel the Indian economy.
For the average Indian student, government official, or entrepreneur, Sarvam AI provides a tool that actually “gets” them. It understands why a user might switch between Hindi and English mid-sentence, a phenomenon known as code-switching and responds with the same cultural fluidity.
The Dawn of a New AI Era
The rise of Sarvam AI marks the end of India’s “user-only” era in the AI revolution. With the launch of the 30B and 105B models, India has proven that it can build foundational technology that competes on the global stage.
Whether it becomes as famous as ChatGPT remains to be seen, but Sarvam AI has already achieved its primary mission: it has made AI a sovereign, local, and accessible reality for every Indian. As the infrastructure grows and the “2047 Tax Holiday” lures more global tech to Indian shores, Sarvam is perfectly positioned to be the brain powering India’s trillion-dollar digital dream.
About the Author
