TL;DR
Bengaluru's Sarvam AI has launched Sarvam-30B and Sarvam-105B, two large language models optimized for advanced reasoning and enterprise use. These models aim to lower inference costs by focusing on "efficient thinking," allowing Indian firms to deploy sophisticated AI domestically rather than relying on global APIs.
Vichaarak Perspective: The "Reasoning" Frontier
The debut of Sarvam-105B signals that India is no longer content to be a mere wrapper-service for OpenAI or Anthropic. By benchmarking against Gemma, Mistral, and GPT-OSS, Sarvam is signaling a move toward sovereign AI that understands localized, high-context business needs better than its global cousins.
The Contrarian View: Building foundational models is a billionaire's poker game. While Sarvam’s "efficient thinking" and lower token usage are compelling, the real barrier to entry is no longer parameter count—it's proprietary data and vertical-specific moats. Unless Sarvam can lock in India's top 500 enterprises with datasets that global models haven't crawled, they risk being "Mistral-ed"—hailed for their tech but ultimately squeezed by the hyperscalers' distribution power.