The gap between the best open-weight AI model and the best closed model has narrowed to a few points, while the price gap runs one-to-two orders of magnitude, creating a major opening for Indian AI. The National AI Mission should fund builders who can seize this opportunity. On the Artificial Analysis Intelligence Index, Moonshot’s Kimi K3 scores 57 against about 61 for the leading closed model, while Z.ai’s GLM-5.2 reaches 51 under a permissive licence. In Bengaluru, Sarvam announced a trillion-plus parameter model built from scratch, priced its 105-billion parameter model at $0.80 per million tokens against $4.50 for OpenAI’s GPT-5.4 Mini, and launched an inference service hosted in India. Kimi K3, a 2.8-trillion parameter model whose weights were published in late July, ranks third overall on the index, though at 1.56 terabytes it is too large for most buyers to host. GLM-5.2 posts 51 under an MIT licence and runs on buyer-controlled infrastructure. DeepSeek’s V4 models score near 44 and cost roughly a tenth of the leading American systems. Alibaba’s Qwen has become the most widely adopted open base globally. On coding, mathematics and reasoning, the strongest Chinese open models trade blows with GPT, Claude and Gemini, while a genuine gap still survives at the absolute frontier.