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China’s latest AI model claims to be even cheaper to use than DeepSeek

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The World Artificial Intelligence Conference kicked off in Shanghai on Saturday, July 26, 2025.

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BEIJING — Chinese companies are making smarter artificial intelligence models that are increasingly cheaper to use, echoing key aspects of DeepSeek’s market-shaking breakthrough.

Startup Z.ai, formerly known as Zhipu, announced Monday that its new GLM-4.5 AI model would cost less than DeepSeek to use. In contrast to the logic underlying existing AI models, Z.ai said its new GLM-4.5 is built on what’s known as “agentic” AI, meaning that the model automatically breaks down a task into sub-tasks in order to complete it more accurately.

The new model is also open sourced, meaning it is free for developers to download and use.

At about half the size of DeepSeek’s model, GLM-4.5 only needs eight Nvidia H20 chips to operate, Z.ai CEO Zhang Peng told CNBC on Monday.

That’s the chip Nvidia customized for China in order to comply with U.S. export controls. The chipmaker said this month that the U.S. will allow it to resume those China sales after a three-month pause, but it’s unclear when those shipments will begin.

Zhang said the company doesn’t need to buy more of the chips as it has enough computing power for now, but declined to share how much Z.ai spent on training the AI model. Details will be released later, he said.

Trump's AI strategy understands 'denying the chips doesn't work': CSIS

Back in January, DeepSeek had rattled global investors with its apparent ability to defy U.S. chip restrictions and create an AI model that not only rivaled U.S.-based OpenAI’s ChatGPT, but also undercut it in training and operating costs.

DeepSeek claimed training costs for its V3 model were less than $6 million, although some analysts said that figure was based on the company’s hardware spend of more than $500 million over time.

Z.ai said that for its new GLM-4.5 model, it would charge 11 cents per million input tokens versus 14 for DeepSeek R1; and 28 cents per million output tokens versus $2.19 for DeepSeek. Tokens are a way of measuring data for AI model processing.

Earlier this month, Alibaba-backed Moonshot released Kimi K2, which claimed to beat OpenAI’s ChatGPT and Anthropic’s Claude on certain coding capabilities. Kimi K2 charges 15 cents for every 1 million input tokens, and $2.50 per 1 million output tokens, according to its website.

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In late June, OpenAI named Zhipu in a warning about Chinese AI progress. The U.S. has also added the startup to its entity list that restricts American companies from doing business with it.

Z.ai launched in 2019 and is reportedly planning an initial public offering in Greater China.

The startup has raised more than $1.5 billion from investors including Alibaba, Tencent and Qiming Venture Partners, according to PitchBook. Aramco-backed Prosperity7 Ventures as well as municipal funds from the cities of Hangzhou and Chengdu are also among Z.ai’s backers, the database showed.

In the last few weeks, several other Chinese companies have announced new, open-source AI models. During the World AI Conference in Shanghai, Tencent released the HunyuanWorld-1.0 model for generating three-dimensional scenes for game development. Last week, Alibaba announced its Qwen3-Coder model for writing computer code.

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Treasury Yields Rise as Fed Cut Expectations Shift

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Treasury Yields Rise as Fed Cut Expectations Shift

Fixed-income markets recorded significant re-pricing during the week ending July 25, 2026, as a convergence of strong labor market metrics and surging energy costs drove U.S. Treasury yields higher across all maturities. The benchmark 10-year Treasury yield climbed toward 4.70%, reaching its highest point in several months. Institutional bond investors rapidly adjusted portfolio durations as expectations for near-term interest rate cuts by the Federal Reserve faded in response to inflation concerns.

The upward shift in sovereign yields reflects a broader fundamental reassessment of global monetary policy. Earlier in the quarter, money markets had priced in a series of rate reductions designed to support economic activity. However, with initial jobless claims falling to 187,000 and crude oil breaching $100 per barrel, fixed-income traders are pricing in a ‘higher-for-longer’ interest rate environment. The inversion between short-term Treasury bills and long-term bonds narrowed, indicating a shift toward term premium expansion.

Rising Treasury yields present both challenges and opportunities for institutional wealth managers. While commercial lenders and mortgage origination volumes face headwinds from elevated borrowing costs, fixed-income investors are locking in attractive real yields on high-quality sovereign and investment-grade corporate bonds. Institutional debt issuers, conversely, are recalibrating their capital structures, opting for shorter-term refinancing instruments or private credit facilities to avoid committing to elevated long-term coupon rates.

Navigating the current bond market landscape demands strict duration management and credit selection. Wealth advisors recommend maintaining flexible fixed-income allocations, combining short-duration Treasuries with inflation-protected securities (TIPS) to shield capital against potential energy-driven inflation spikes while earning dependable nominal income.

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Private Credit Expansion Transforms Corporate Loans

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Private Credit Expansion Transforms Corporate Loans

Private credit markets reached a pivotal milestone during the week ending July 25, 2026, as non-bank direct lending consortiums captured a record share of middle-market corporate debt originations. With commercial banks maintaining conservative credit standards and public bond yields remaining elevated, corporate borrowers are increasingly turning to private fund managers for customized capital solutions. This expansion marks a permanent structural shift in enterprise finance, establishing private credit as a primary pillar of institutional corporate liquidity.

The acceleration of private credit deals is driven by speed, deal certainty, and flexible terms. Unlike traditional syndicated bank loans that require lengthy underwriting, credit rating approvals, and public roadshows, private direct lenders can structure tailored financing packages within days. Middle-market firms facing upcoming debt maturities are utilizing private debt facilities to execute recapitalizations, strategic acquisitions, and growth capital deployments without risking execution delay in public markets.

However, financial regulators and central bank supervisors are scrutinizing the sector’s rapid growth. Supervisory agencies are evaluating potential systemic risks associated with non-bank leverage, valuation transparency, and liquidity mismatches during economic downturns. Despite regulatory interest, major pension funds, insurance firms, and sovereign wealth entities continue to expand capital allocations to private credit funds, attracted by reliable floating-rate yields that outperform public fixed-income benchmarks.

As private credit matures into a dominant asset class, corporate chief financial officers must evaluate non-bank lenders alongside traditional banking relationships. Direct lending partnerships provide valuable balance sheet resilience, enabling companies to secure flexible financing terms even during periods of public market turbulence.

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Tokenized Debt Shifts How Corporate Manage Short Term Liquidity

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Tokenized Debt Shifts Corporate Liquidity

The landscape of institutional debt markets is undergoing a profound structural shift on July 21, 2026, as major corporate issuers and commercial banks rapidly accelerate the deployment of tokenized debt instruments. Data published by leading capital market consortiums indicates that primary issuances of digital commercial paper and tokenized corporate bonds have reached record volumes this month. By moving legacy debt origination, underwriting, and secondary distribution onto permissioned distributed ledgers, corporate treasurers are unlocking unprecedented operational flexibility and instantaneous cross-border liquidity.

The adoption of tokenized debt is fundamentally altering how enterprise balance sheets manage short-term liquidity needs. Traditional corporate bond settlement cycles historically required multi-day clearing processes involving numerous intermediaries, custodial entities, and clearinghouses. Through programmable smart contracts on distributed ledgers, issuers can now execute atomic settlement—enabling continuous, 24/7 access to institutional capital pools. This instantaneous clearing mechanism drastically reduces counterparty risk, eliminates costly settlement friction, and allows treasury teams to dynamically optimize working capital in real time.

A major catalyst driving this institutional migration is the establishment of comprehensive digital asset regulatory frameworks across major financial hubs. Clear legal guidelines regarding ledger-based securities ownership have provided institutional compliance officers with the regulatory confidence necessary to transition multi-billion-dollar liquidity facilities onto digital platforms. Furthermore, the integration of automated regulatory reporting directly into token smart contracts simplifies ongoing compliance audits, ensuring that secondary market trades automatically enforce investor accreditation limits and tax withholding requirements.

For chief financial officers and institutional portfolio managers, tokenized debt represents a fundamental evolution in fixed-income strategy. Companies that embrace ledger-based debt structures gain direct access to a broader, global base of digital-native institutional investors while substantially reducing borrowing overhead. As ledger interoperability continues to improve across global exchanges, tokenized debt is poised to become the standard infrastructure for global corporate finance.

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