{"id":994915,"date":"2026-08-13T09:27:27","date_gmt":"2026-08-13T13:27:27","guid":{"rendered":"https:\/\/www.marketnewsdesk.com\/index.php\/vegashares-announces-launch-of-the-ai-inference-etf-cgpt-and-the-ai-thermal-cooling-power-management-etf-cool\/"},"modified":"2026-08-13T09:27:27","modified_gmt":"2026-08-13T13:27:27","slug":"vegashares-announces-launch-of-the-ai-inference-etf-cgpt-and-the-ai-thermal-cooling-power-management-etf-cool","status":"publish","type":"post","link":"https:\/\/www.marketnewsdesk.com\/index.php\/vegashares-announces-launch-of-the-ai-inference-etf-cgpt-and-the-ai-thermal-cooling-power-management-etf-cool\/","title":{"rendered":"VegaShares Announces Launch of the AI Inference ETF (CGPT) and the AI Thermal, Cooling & Power Management ETF (COOL)"},"content":{"rendered":"

<\/p>\n

VegaShares Announces Launch of the AI Inference ETF (CGPT) and the AI Thermal, Cooling & Power Management ETF (COOL)<\/b><\/p>\n

CGPT and COOL provide targeted exposure to two layers of the AI infrastructure buildout: the inference stack that runs trained models, and the power and cooling that keep high-density data centers online.<\/i><\/p>\n

NEW YORK–(BUSINESS WIRE<\/a>)–VegaShares<\/a> (\u201cVega\u201d), a leading derivatives- and thematic-focused ETF provider, announced the launch of two thematic ETFs: the VegaShares AI Inference ETF (Nasdaq: CGPT)<\/b> and the VegaShares AI Thermal, Cooling & Power Management ETF (Nasdaq: COOL)<\/b>.<\/p>\n

\nThe VegaShares AI Inference ETF (Nasdaq: CGPT)<\/b> seeks capital appreciation by investing in companies that make the chips, networking, and memory hardware used to run AI models and generate responses. The Fund invests across AI processors, custom AI chips, memory and interconnect chips.<\/p>\n

\nTraining a model is a bounded compute expense, incurred each time a new model version is built or retrained. Inference is different: it happens every time that model is used, whether that is a chatbot answering a question, a bank\u2019s fraud model screening a transaction, or a sensor on a factory floor flagging a defect. That difference is what makes inference infrastructure a separate investment case from training infrastructure: the companies supplying the chips, networking, and memory behind it generate revenue that scales with usage, not with how many models get built. According to a Morgan Stanley analysis, the inference phase, running a trained model to answer a question, screen a transaction, or make a prediction, could represent a larger opportunity than the initial AI training market.<\/p>\n

\nThe VegaShares AI Inference ETF gives investors targeted access to the post-training segment of the AI market.<\/p>\n

CGPT Top Fifteen Holdings:<\/span><\/b><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\n

Company Name<\/b><\/p>\n<\/td>\n

\n

Ticker<\/b><\/p>\n<\/td>\n

\n

Weight<\/b><\/p>\n<\/td>\n<\/tr>\n

\n

\nCerebras Systems Inc.<\/p>\n<\/td>\n

\n

\nCBRS US<\/p>\n<\/td>\n

\n

\n9.0%<\/p>\n<\/td>\n<\/tr>\n

\n

\nCredo Technology Group Holding Ltd.<\/p>\n<\/td>\n

\n

\nCRDO US<\/p>\n<\/td>\n

\n

\n8.5%<\/p>\n<\/td>\n<\/tr>\n

\n

\nAstera Labs Inc.<\/p>\n<\/td>\n

\n

\nALAB US<\/p>\n<\/td>\n

\n

\n8.0%<\/p>\n<\/td>\n<\/tr>\n

\n

\nNVIDIA Corporation<\/p>\n<\/td>\n

\n

\nNVDA US<\/p>\n<\/td>\n

\n

\n7.5%<\/p>\n<\/td>\n<\/tr>\n

\n

\nCambricon Technologies Corporation Ltd.<\/p>\n<\/td>\n

\n

\n688256 CH<\/p>\n<\/td>\n

\n

\n7.0%<\/p>\n<\/td>\n<\/tr>\n

\n

\nAdvanced Micro Devices Inc.<\/p>\n<\/td>\n

\n

\nAMD US<\/p>\n<\/td>\n

\n

\n4.5%<\/p>\n<\/td>\n<\/tr>\n

\n

\nAlchip Technologies Ltd.<\/p>\n<\/td>\n

\n

\n3661 TT<\/p>\n<\/td>\n

\n

\n4.5%<\/p>\n<\/td>\n<\/tr>\n

\n

\nBroadcom Inc.<\/p>\n<\/td>\n

\n

\nAVGO US<\/p>\n<\/td>\n

\n

\n4.5%<\/p>\n<\/td>\n<\/tr>\n

\n

\nGlobal Unichip Corporation<\/p>\n<\/td>\n

\n

\n3443 TT<\/p>\n<\/td>\n

\n

\n4.5%<\/p>\n<\/td>\n<\/tr>\n

\n

\nHygon Information Technology Co. Ltd.<\/p>\n<\/td>\n

\n

\n688041 CH<\/p>\n<\/td>\n

\n

\n4.5%<\/p>\n<\/td>\n<\/tr>\n

\n

\nMarvell Technology Inc.<\/p>\n<\/td>\n

\n

\nMRVL US<\/p>\n<\/td>\n

\n

\n4.5%<\/p>\n<\/td>\n<\/tr>\n

\n

\nMicron Technology Inc.<\/p>\n<\/td>\n

\n

\nMU US<\/p>\n<\/td>\n

\n

\n4.5%<\/p>\n<\/td>\n<\/tr>\n

\n

\nSK hynix Inc.<\/p>\n<\/td>\n

\n

\nSKHY US<\/p>\n<\/td>\n

\n

\n4.5%<\/p>\n<\/td>\n<\/tr>\n

\n

\nIluvatar CoreX<\/p>\n<\/td>\n

\n

\n09903 HK<\/p>\n<\/td>\n

\n

\n4.0%<\/p>\n<\/td>\n<\/tr>\n

\n

\nSamsung Electronics Co. Ltd.<\/p>\n<\/td>\n

\n

\nSMSN LI<\/p>\n<\/td>\n

\n

\n4.0%<\/p>\n<\/td>\n<\/tr>\n

\n\n\u00a0<\/td>\n<\/tr>\n
\n

Holdings are subject to change.<\/i><\/p>\n<\/td>\n<\/tr>\n<\/table>\n

\nThe VegaShares AI Thermal, Cooling & Power Management ETF (Nasdaq: COOL)<\/b> seeks capital appreciation by investing in global companies that generate significant revenue from the cooling, power delivery, and thermal management systems required to operate high-density AI data centers. The Fund invests across server liquid cooling, power supplies and power shelves, battery backup and rack-level power distribution, and power semiconductors.<\/p>\n

\nTraining and running large models often means packing more chips into less space, and each chip simultaneously requires the delivery of power and the removal of heat. Spending on liquid cooling equipment is projected to grow 45 to 50% a year through 2030 according to a McKinsey report, more than three times the pace of traditional air-cooling equipment.<\/p>\n

COOL Top Fifteen Holdings:<\/span><\/b><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\n

Company Name<\/b><\/p>\n<\/td>\n

\n

Ticker<\/b><\/p>\n<\/td>\n

\n

Weight<\/b><\/p>\n<\/td>\n<\/tr>\n

\n

\nVertiv Holdings Co.<\/p>\n<\/td>\n

\n

\nVRT US<\/p>\n<\/td>\n

\n

\n9.5%<\/p>\n<\/td>\n<\/tr>\n

\n

\nAsia Vital Components Co. Ltd.<\/p>\n<\/td>\n

\n

\n3017 TT<\/p>\n<\/td>\n

\n

\n9.0%<\/p>\n<\/td>\n<\/tr>\n

\n

\nJentech Precision Industrial Co. Ltd.<\/p>\n<\/td>\n

\n

\n3653 TT<\/p>\n<\/td>\n

\n

\n8.5%<\/p>\n<\/td>\n<\/tr>\n

\n

\nAuras Technology Co. Ltd.<\/p>\n<\/td>\n

\n

\n3324 TT<\/p>\n<\/td>\n

\n

\n7.0%<\/p>\n<\/td>\n<\/tr>\n

\n

\nSunonwealth Electric Machine Industry Co. Ltd.<\/p>\n<\/td>\n

\n

\n2421 TT<\/p>\n<\/td>\n

\n

\n6.0%<\/p>\n<\/td>\n<\/tr>\n

\n

\nAdvanced Energy Industries Inc.<\/p>\n<\/td>\n

\n

\nAEIS US<\/p>\n<\/td>\n

\n

\n4.5%<\/p>\n<\/td>\n<\/tr>\n

\n

\nChicony Power Technology Co. Ltd.<\/p>\n<\/td>\n

\n

\n6412 TT<\/p>\n<\/td>\n

\n

\n4.5%<\/p>\n<\/td>\n<\/tr>\n

\n

\nNavitas Semiconductor Corporation<\/p>\n<\/td>\n

\n

\nNVTS US<\/p>\n<\/td>\n

\n

\n4.5%<\/p>\n<\/td>\n<\/tr>\n

\n

\nNidec Chaun-Choung Technology Corporation<\/p>\n<\/td>\n

\n

\n6230 TT<\/p>\n<\/td>\n

\n

\n4.5%<\/p>\n<\/td>\n<\/tr>\n

\n

\nSanyo Denki Co. Ltd.<\/p>\n<\/td>\n

\n

\n6516 JP<\/p>\n<\/td>\n

\n

\n4.5%<\/p>\n<\/td>\n<\/tr>\n

\n

\nShenzhen Envicool Technology Co. Ltd.<\/p>\n<\/td>\n

\n

\n002837 CH<\/p>\n<\/td>\n

\n

\n4.5%<\/p>\n<\/td>\n<\/tr>\n

\n

\nVicor Corporation<\/p>\n<\/td>\n

\n

\nVICR US<\/p>\n<\/td>\n

\n

\n4.5%<\/p>\n<\/td>\n<\/tr>\n

\n

\nFSP Technology Inc.<\/p>\n<\/td>\n

\n

\n3015 TT<\/p>\n<\/td>\n

\n

\n3.5%<\/p>\n<\/td>\n<\/tr>\n

\n

\nTaiSol Electronics Co. Ltd.<\/p>\n<\/td>\n

\n

\n3338 TT<\/p>\n<\/td>\n

\n

\n3.5%<\/p>\n<\/td>\n<\/tr>\n

\n

\nADDA Corporation<\/p>\n<\/td>\n

\n

\n3071 TT<\/p>\n<\/td>\n

\n

\n3.0%<\/p>\n<\/td>\n<\/tr>\n

\n\n\u00a0<\/td>\n<\/tr>\n
\n

Holdings are subject to change.<\/i><\/p>\n<\/td>\n<\/tr>\n<\/table>\n

\n\u201cToday we are launching two funds, CGPT and COOL, that deliver exposure to two distinct layers of the AI buildout: inference and cooling, respectively,\u201d said Adam Stempel, Co-Founder of VegaShares ETFs. \u201cCGPT invests in the chips, networking, and memory that run trained models in production, and COOL invests in the thermal, power, and cooling systems behind high-density AI data centers. Together, the two funds give investors targeted access to parts of the AI buildout that sit underneath the applications getting the headlines.\u201d<\/p>\n

\nFor more information on the funds, please visit VegaSharesETFs.com\/COOL<\/a> and VegaSharesETFs.com\/CGPT<\/a>.<\/p>\n

About VegaShares<\/b><\/p>\n

\nVegaShares specializes in derivatives-based ETFs and other innovative investment strategies. Developed by institutional experts, VegaShares blends quantitative research with disciplined risk management to create liquid, exchange-traded tools for modern investors seeking efficiency, precision, and performance.<\/p>\n

Before investing, carefully consider the fund\u2019s investment objectives, risks, and charges and expenses. The prospectus and summary prospectus contain this and other important information and may be obtained by visiting VegaSharesETFs.com or calling 1-888-862-3299. Read it carefully before investing.<\/b><\/p>\n

\nThe funds, their investment adviser Tidal Investments LLC (the \u201cAdviser\u201d), their investment sub-adviser Vega Capital Partners LLC (the \u201cSub-Adviser\u201d), and their distributor do not provide tax, legal, or investment advice. Investors should consult a financial professional regarding an investment in the funds and should carefully consider the funds\u2019 investment objectives, risks, charges, and expenses before investing.<\/p>\n

\nThe VegaShares AI Inference ETF and the VegaShares AI Thermal, Cooling & Power Management ETF are each a series of Tidal Trust IV (the \u201cTrust\u201d) and are exchange traded funds. Shares of the funds are bought and sold at market price (not net asset value) and are not individually redeemed from the funds. Brokerage commissions and bid\/ask spreads will reduce returns.<\/p>\n

Investing involves risk, including the loss of principal.<\/b> An investment in a Fund is subject to investment risks; therefore, you may lose money by investing in a Fund. There can be no assurance that a Fund will be successful in meeting its investment objective. A Fund is not intended to be a complete investment program. Generally, each Fund will be subject to the following principal risks:<\/p>\n

Shared Principal Risks<\/b><\/p>\n