Shares of Jio Financial Services climbed sharply on Friday after the Reliance Industries-backed lender reported more than a twofold increase in quarterly profit, boosting investor optimism that the company’s aggressive expansion across lending, payments, insurance, wealth management and asset management is beginning to deliver meaningful financial returns.

The stock rose as much as 6.1% during the session before trimming gains to close 3.1% higher at 242.98 rupees, making it one of the best-performing stocks on India’s benchmark Nifty 50 index, which ended the day 1.09% higher.

The rally followed the company’s first-quarter earnings released on Thursday, which showed net profit more than doubled to 8.3 billion rupees ($86.2 million), driven by broad-based growth across its businesses. The results strengthened investor confidence that Jio Financial is evolving from a company largely dependent on investment income into a diversified financial services platform with expanding operating earnings.

The company was spun off from Mukesh Ambani’s Reliance Industries and listed on Indian exchanges in 2023. Since then, it has pursued an ambitious strategy to build a full-stack financial ecosystem spanning consumer and business lending, digital payments, insurance distribution, asset management, wealth management and financial technology services.

The latest results suggest that the strategy is beginning to gain traction.

“Jio Financial has a very large balance sheet and a very strong parent. Since financial services is also a rapidly expanding space, I think the next couple of years will be good for them,” said Avinash Gorakshakar, founder of Avinash Mentor Research Services.

“The traction is now being reflected in the company’s numbers. Earlier it was only their treasury income that was generating revenue and profit. But now operationally, most of the divisions that they have started have begun contributing in terms of revenue,” he added.

Shift from Treasury Income to Operating Earnings

One of the most significant takeaways from the quarter is the company’s gradual transition away from dependence on treasury income generated from its sizeable cash reserves following the demerger from Reliance Industries.

For several quarters after listing, investors questioned whether Jio Financial could convert its substantial capital base into a scalable operating business. The latest earnings indicate that lending, insurance, and other financial services are increasingly contributing to revenue and profit, reducing reliance on investment income and improving the quality of earnings.

This transition is viewed positively because recurring operating income generally commands higher valuation multiples than treasury-driven earnings.

Analysts say one of Jio Financial’s biggest advantages remains its access to Reliance Industries’ vast digital ecosystem.

Through Reliance’s retail operations, telecom arm Jio, e-commerce businesses, and digital platforms, Jio Financial has potential access to hundreds of millions of consumers and millions of merchants. That allows the company to cross-sell loans, insurance products, payment services, and investment products at significantly lower customer acquisition costs than traditional financial institutions.

The ability to leverage existing customer relationships also provides valuable consumer data that can improve underwriting, personalize financial products, and strengthen customer retention. Unlike many fintech startups that spend heavily to acquire customers, Jio Financial can rely on the broader Reliance ecosystem to accelerate growth while maintaining greater cost efficiency.

Lending Business Emerging As A Major Growth Engine

Brokerage Motilal Oswal highlighted the rapid expansion of Jio Credit, the company’s lending subsidiary, which has scaled quickly since its launch. According to the brokerage, gross assets under management have already exceeded 300 billion rupees, underscoring strong demand for the company’s lending products.

As India’s credit penetration remains well below that of many developed economies, analysts see significant room for sustained expansion in retail, consumer, and small-business lending. Motilal Oswal forecasts Jio Financial’s assets under management will grow at an 85% compound annual growth rate between fiscal years 2026 and 2028, while profit is expected to increase at an even faster 145% CAGR over the same period.

Such projections reflect expectations that the company is entering a period where scale benefits, cross-selling opportunities, and operating leverage could accelerate earnings growth.

Insurance and Asset Management Gaining Momentum

Jefferies said the quarterly performance was supported not only by customer growth but also by continued progress in Jio Financial’s insurance business.

Insurance represents one of India’s fastest-growing financial sectors, with penetration still relatively low compared with developed markets. Rising household incomes, greater financial awareness, and expanding digital distribution channels are expected to drive long-term growth in life, health, and general insurance.

Asset and wealth management also represent major long-term opportunities as India’s expanding middle class allocates more savings toward mutual funds, retirement products, and other investment vehicles. Together, these businesses provide recurring fee income that complements lending revenue and helps diversify earnings.

Jio Financial is expanding at a time when India’s financial sector is undergoing rapid structural change.

Digital payments continue to grow at one of the fastest rates globally, supported by the widespread adoption of the Unified Payments Interface (UPI). At the same time, rising formal employment, increasing smartphone penetration and government-backed digital infrastructure are accelerating financial inclusion and expanding demand for credit, insurance and investment products.

These trends are creating significant opportunities for companies capable of offering multiple financial services through integrated digital platforms. Industry analysts believe scale will become increasingly important as competition intensifies among banks, non-bank financial companies, fintech firms, and technology companies entering financial services.

Friday’s share price rally suggests investors are increasingly focusing on Jio Financial’s long-term earnings potential rather than valuing it solely on its cash holdings or treasury income.

The company enjoys several structural advantages, including strong financial backing from Reliance Industries, one of India’s largest corporate groups, a rapidly expanding customer base, significant capital available to fund growth, and the ability to leverage Reliance’s extensive digital and retail ecosystem.

However, analysts note that sustaining the current valuation will depend on management’s ability to continue expanding its loan book while maintaining asset quality, grow fee-based businesses such as insurance and wealth management, and execute its strategy without compromising profitability.

If the company successfully scales these businesses while preserving credit discipline, many analysts believe Jio Financial could emerge as one of India’s leading integrated financial institutions over the next decade, challenging both traditional lenders and digital-first fintech platforms. The latest quarterly results provide one of the clearest indications yet that the company’s transformation from a newly listed holding company into a diversified financial services powerhouse is beginning to gather pace.

Chinese artificial intelligence startup Moonshot has unveiled Kimi K3, a 2.8 trillion-parameter model that it says is the world’s largest open-weight AI system, intensifying competition between Chinese and U.S. AI developers as Beijing’s open-source ecosystem rapidly closes the technological gap with Silicon Valley.

The launch represents another milestone in China’s accelerating AI development and reinforces a broader trend reshaping the global industry. Rather than merely catching up to U.S. leaders, Chinese AI companies are increasingly competing at the frontier through open-weight models that combine advanced capabilities with substantially lower deployment costs.

Moonshot said Kimi K3 delivers performance approaching Anthropic’s frontier Fable models, while offering enterprises and developers the flexibility to download, customize and deploy the model themselves, an attractive proposition as businesses seek alternatives to expensive proprietary AI services.

The announcement comes just weeks after Anthropic’s Fable and Mythos models were withdrawn from non-U.S. markets following U.S. government security restrictions, a development that has created new opportunities for Chinese developers to expand internationally, particularly in emerging markets.

Kimi K3 is the latest example of how Chinese AI firms are shortening the innovation cycle.

Companies including Moonshot, Z.ai, MiniMax, DeepSeek, Alibaba, Meituan and Zhipu have released capable foundation models over the past year, challenging the long-held assumption among Western analysts that Chinese AI technology trails American competitors by six months or more.

That perception has steadily weakened as Chinese models have demonstrated competitive performance across coding, reasoning, mathematics, and agent-based tasks while often costing significantly less to deploy.

The shift has been driven partly by China’s embrace of open-weight AI, allowing developers and enterprises to build customized applications without relying on proprietary cloud services operated by U.S. technology companies.

Unlike closed models from OpenAI, Anthropic and Google, open-weight systems provide access to model weights, enabling organizations to fine-tune models for specialized tasks, deploy them within private infrastructure and avoid recurring API fees.

A 2.8 Trillion-Parameter Model

Moonshot said Kimi K3 is the first publicly released open-weight model to approach the 3 trillion-parameter threshold.

Parameters are the internal mathematical variables an AI model learns during training. While a larger parameter count generally denotes greater model capacity, it does not automatically translate into superior performance. Training quality, architecture, data, and inference optimization are equally important.

Even so, Kimi K3’s scale places it among the largest AI models ever announced.

The model includes a one-million-token context window, allowing it to process and retain extraordinarily large volumes of text, code and documentation within a single prompt. That capability makes the model particularly suited for enterprise workloads involving extensive technical documentation, software development, legal analysis, scientific research and long-form reasoning.

Moonshot said the model was designed specifically for advanced reasoning, long-horizon coding and knowledge-intensive work requiring sustained contextual understanding.

Competitive Benchmark Performance

Moonshot claims Kimi K3 delivers performance approaching some of the world’s strongest proprietary AI systems.

According to the company, the model performed competitively with Anthropic’s Fable 5 while substantially outperforming Anthropic Opus 4.8, OpenAI’s GPT-5.6 Sol and GPT-5.5 in GPU kernel optimization, an important measure of how efficiently AI software utilizes computing hardware to maximize throughput and minimize latency.

Independent benchmark organizations also reported encouraging results.

Arena.ai ranked Kimi K3 first in web interface-building capability, while Vals AI placed it second overall behind Fable 5 and ahead of GPT-5.6 Sol.

Artificial Analysis found the model delivered performance broadly comparable to OpenAI’s GPT-5.5 and Anthropic’s Opus 4.8, particularly on evaluations measuring complex multi-step reasoning and agentic workflows.

Those results suggest Chinese models are becoming increasingly competitive across a broader range of enterprise applications rather than excelling only in isolated benchmarks.

Efficiency Becoming As Important As Scale

Moonshot said Kimi K3 incorporates two major architectural improvements designed to increase computational efficiency while enabling longer autonomous coding sessions with minimal human supervision.

That represents an important shift in AI development. Rather than simply building ever-larger models, leading developers are increasingly focused on improving inference efficiency, reducing latency and lowering deployment costs, all of which determine the commercial viability of large language models.

Lian Jye Su, chief analyst at Omdia, said cost remains one of China’s biggest competitive advantages.

“They can be run at a fraction of the cost that OpenAI charges its clients,” he said, while cautioning that model size alone does not guarantee superior performance.

Lower operating costs have become an increasingly powerful selling point as enterprises seek to scale AI deployment without dramatically increasing computing budgets.

Despite being open-weight, Kimi K3 is unlikely to be deployed locally by most organizations.

Ryan Fedasiuk, a fellow at the American Enterprise Institute, noted that operating a 2.8 trillion-parameter model would require computing infrastructure costing hundreds of thousands of dollars, placing self-hosting beyond the reach of most individual developers and smaller businesses.

Instead, the model is expected to be deployed primarily through cloud providers, enterprise AI platforms and specialized infrastructure operators.

Investors reacted quickly to the announcement.

Shares of Hong Kong-listed AI companies Zhipu and MiniMax fell 27.7% and 16.5%, respectively, before the close of trading, reflecting concerns that Moonshot’s technological lead could intensify competition within China’s increasingly crowded AI sector.

The reaction underscores how quickly competitive dynamics are evolving as Chinese developers release new frontier models at an accelerating pace.

Before Kimi K3, China’s largest publicly known models included Meituan’s LongCat-2.0 and DeepSeek V4-Pro, each containing approximately 1.6 trillion parameters. Several other Chinese developers have now crossed the trillion-parameter threshold, signaling that frontier-scale AI development is becoming increasingly widespread within China’s technology sector.

Direct comparisons with U.S. models remain difficult because companies, including OpenAI and Anthropic, do not disclose parameter counts for GPT-5.5, Fable or Mythos. Instead, performance comparisons increasingly rely on independent benchmark evaluations rather than model size alone.

Moonshot has emerged as one of China’s fastest-growing AI startups, supported by major investors including Alibaba and Tencent.

The company has expanded aggressively over the past year as competition intensifies among Chinese AI developers seeking to establish leadership in both domestic and international markets.

Bloomberg reported recently that Moonshot is seeking $2 billion in new financing at a valuation of approximately $30 billion ahead of a potential Hong Kong initial public offering.

Kimi K3’s release is seen as another indication that the competitive balance in artificial intelligence is evolving. While U.S. companies continue to lead in frontier proprietary models, Chinese developers have rapidly established themselves as leaders in the open-weight ecosystem by combining strong performance with lower deployment costs and greater customization.

That strategy is proving attractive to enterprises seeking greater control over AI infrastructure, particularly in regions where access to advanced U.S. models has become more restricted because of export controls and national security policies. The result is a bifurcated AI market: one centered on proprietary frontier systems from U.S. firms, and another built around increasingly powerful open-weight models from China.