Chinese President Xi Jinping has proposed creating a BRICS open-source artificial intelligence community, offering member countries shared large language models, training programs, and cloud infrastructure as an alternative to proprietary AI systems controlled by American companies like OpenAI and Anthropic. The announcement at the BRICS Summit in New Delhi on Sunday represents Beijing's latest effort to position Chinese AI technology as a more accessible option for developing nations, even as questions linger about the long-term implications for safety and sovereignty.

What's the Difference Between Open-Weight and Closed AI Models?

To understand why Xi's proposal matters, it helps to know how AI models are structured differently. An open-weight model publishes its learned parameters, the numerical values a model has trained into itself, allowing anyone to download, adapt, or run the model on their own computers. Closed models like ChatGPT or Claude keep those weights behind an application programming interface (API), meaning users rent access through a subscription.

Chinese companies have already released several open-weight models, including DeepSeek and Alibaba's Qwen family, which developers can download and run on their own infrastructure. This differs fundamentally from closed models, where users depend on the company's servers and must pay for each query.

The trade-off is significant. Open-weight models require powerful computers and expensive memory, known as compute, to run locally. Closed models handle that infrastructure cost internally and pass it to users through subscription fees. For developing countries with limited budgets, open-weight models offer a path to AI capability without ongoing licensing fees.

Why Is Cost Such a Compelling Argument for Open Models?

The economics tell a striking story. DeepSeek, a Chinese AI lab, trained a frontier-class model, meaning a state-of-the-art system comparable to the most advanced models available, for a reported $5.6 million under US export restrictions on advanced chips. Researchers at UC Berkeley subsequently replicated comparable reasoning capability for around $50.

For India, the scale gap is even more dramatic. India's five-year IndiaAI Mission budget of roughly $1.2 billion is approximately what OpenAI spends in six months. At that disparity, open-weight models represent the only realistic route for developing countries to build sophisticated AI capability without depending entirely on foreign providers.

A 2025 survey by Emeritus found that 96% of Indian professionals using AI or generative AI at work rely overwhelmingly on foreign models and foreign compute infrastructure, given the early stage of India's own foundation-model ecosystem. Open-weight releases would allow Indian institutions to download, fine-tune, host, and audit models domestically without requiring a US API contract or an export license that could be rescinded at any time.

How Does Xi's Proposal Fit Into Global AI Competition?

Xi's announcement comes as China has stepped up outreach to developing countries on AI. At the World Artificial Intelligence Conference in Shanghai in July, Xi announced 5,000 AI training and seminar opportunities for developing countries over five years and proposed AI application cooperation centers with groupings including BRICS, ASEAN, and the African Union.

The BRICS proposal specifically includes support for cooperation on large language models, specialized AI seminars and training courses, and what Xi described as an open ecosystem for AI. He also proposed setting up a BRICS digital ecosystem cloud platform and expanding cooperation on digital skills, technology exchanges, and intelligent manufacturing.

However, the proposal has not yet been formally adopted as a BRICS-wide program. The New Delhi Declaration issued after the summit does not mention the proposed open-source community or cloud platform, though it does commit BRICS countries more broadly to cooperation on improving access to AI resources while focusing on safety, security, reliability, and inclusiveness.

Steps to Understanding the Strategic Implications of Open-Weight AI

• Sovereignty and Access: Open-weight models allow countries to download and run AI systems domestically without depending on foreign API contracts or export licenses, reducing concentration of AI capacity in a handful of California-based labs.
• Language and Cultural Adaptation: India's 22 scheduled languages are commercially unattractive to closed foundation-model providers, whose training data and safety evaluations are chronically underweight on Indic material. Open-weight models enable universities and public bodies to adapt existing systems for local languages.
• Liability and Safety Concerns: Open-weight releases are effectively irreversible once published online. Malicious fine-tuning can strip built-in safety guardrails from an open-weight model in hours, and responsibility becomes distributed across the original releaser, intermediate fine-tuners, deployers, and end users with no clear locus of liability.

What Does This Mean for India's AI Strategy?

India has positioned itself as a voice for the Global South on AI access. At the AI Impact Summit earlier this year, India and France framed what they called a "third way" as a governance philosophy for AI, built on three pillars: strategic autonomy, shared principles aligned with democratic values and human rights, and collaborative ecosystems built on open-access infrastructure and privacy-preserving data sharing.

Xi's proposal uses similar vocabulary and applies it to a framework Beijing would lead. The proposal fits the collaborative ecosystems plank most closely, offering pooled compute, shared foundation models, joint training courses, and research collaboration across BRICS members, much the same shape of infrastructure India and France proposed in February.

Yet the proposal poses a problem from a strategic autonomy perspective. India built that pillar specifically so it would not have to depend on any small set of dominant tech powers. Joining a Beijing-led open-source community could create a new form of dependence, even if the models themselves are freely available.

There is also a narrower commercial concern. Open-weight models could challenge India's domestic AI companies. Indian model builders like Sarvam and BharatGen face a specific commercial problem that makes their work compelling. But if open-weight models become the operating norm, buyers who might otherwise pay for Indian foundation models can take the next Llama or DeepSeek release for free, weakening the business case for domestic AI development.

When Might This Proposal Actually Become Reality?

For now, Xi's announcement remains a Chinese proposal without formal BRICS backing. Neither the New Delhi Declaration nor other summit documents set out details on which models would be used, where any common cloud infrastructure would be hosted, how data would be handled, or which countries would participate.

However, with China due to take over the BRICS chairship in 2027, Beijing could place these proposals before the grouping again with more formal backing. Those details, when they emerge, will likely determine how substantial the initiative becomes and whether India and other developing nations view it as a genuine path to AI sovereignty or a new form of technological dependence.