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SMCI vs. META: Which AI Infrastructure Stock Has an Edge Now?
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Key Takeaways
META is ramping AI infrastructure with heavy capex, custom chips and large clusters to support its apps.
SMCI's rack-scale systems and modular DCBBS are seeing demand as AI data centers scale capacity worldwide.
SMCI's rapid expansion has lifted inventory and cash cycle days, driving negative free cash flow in FY26.
Super Micro Computer (SMCI - Free Report) and Meta Platforms (META - Free Report) are two prominent AI enablers, playing slightly different roles in the AI infrastructure supply chain. While SMCI positions itself as the supplier of high-performance and energy-efficient servers, META is a hyperscale owner and consumer of AI compute for its family of apps.
Both SMCI and META are likely to gain from the growth of the AI market, which is projected to witness a CAGR 30.6% from 2025 to 2032, reaching a market size of $2407 billion by 2032, per a report by MarketsAndMarkets. Given this scenario, let's closely examine the fundamentals of the two companies, so investors can make an informed bet.
The Case for SMCI Stock
Super Micro Computer provides end-to-end AI rack-scale systems that integrate compute, networking, storage, and liquid cooling for AI data centers. SMCI uses the latest, most powerful and energy-efficient chips developed by NVIDIA and AMD in its servers, making them coveted among global AI data centers and high performance computing players. As new data centers are proliferating and existing ones are scaling up their capacity, the demand for SMCI’s systems is rising.
To enable its customers with rapid scaling, SMCI has introduced Data Center Building Block Solutions (DCBBS), which is modular and ideal for faster set-up. This product is also experiencing high traction among AI data centers and AI factories. The DCBBS incorporates SMCI’s rack-scale compute architecture for large-scale AI training, enterprise AI inference and training, visualization and design, content delivery and virtualization and AI edge.
SMCI’s upcoming facilities in the United States, Taiwan, Malaysia, the Netherlands, and the Middle East are explicitly designed for rack-level production, not just server assembly. SMCI has diversified its offerings by entering into client, edge and consumer AI markets. The company stands to benefit from its enterprise-scale expertise in AI-optimized servers, GPUs, and energy-efficient system design to deliver powerful yet compact solutions for PCs, edge AI, and embedded applications.
SMCI has launched Super AI Station, Supermicro SYS-542T-2R, Supermicro AI PC, Supermicro Edge AI Systems and Supermicro's Fanless Compact Edge System, challenging the existing players in this market for client, edge and consumer AI markets. With this business model at play, the company projects to achieve $36 billion in revenues in fiscal 2026, indicating a massive 64% year-over-year growth.
Nevertheless, to meet the demand, SMCI is expanding rapidly, causing inventory accumulation. SMCI’s first-quarter fiscal 2026 closing inventory was $5.7 billion, up from $4.7 billion in the previous quarter. This situation has spiked its cash conversion cycle from 96 days to 123 days. Negative free cash flow of $950 million for the first quarter of fiscal 2026 is another concern for the company. The Zacks Consensus Estimate for SMCI’s fiscal 2026 earnings shows a modest growth of 2.43%. The estimate has been revised downward in the past 60 days.
Image Source: Zacks Investment Research
The Case for META Stock
Meta Platforms builds, maintains and scales its own data center and technical infrastructure and uses third-party providers to supplement capacity. The company’s data center infrastructure is primarily internally driven to support its family of apps, which require AI training, inference and AI-based ranking systems to stay ahead of its competition. META’s family of apps investments were 79% of its total expenses in 2024, which included data centers and technical infrastructure expenses to develop apps and advertising services.
META has invested in the Meta Training and Inference Accelerator, which are custom-made chips for META’s AI workloads. In late 2024, META launched Catalina open-design, high-powered rack for AI workloads with integrated power, control, compute and interfaces. On the software application front, META is consolidating its smaller, task-specific models into larger, general models, improving performance and efficiency per unit of compute. The company also launched Llama 4, SAM 3, SAM 3D and other LLM models in 2025.
Per its third-quarter 2025 earnings call, Meta is fully focused on becoming a leading frontier AI lab and offering personal superintelligence worldwide. META is preparing for its superintelligence era by aggressively frontloading its building capacity, and in the meantime, using this extra compute power to improve the performance of its existing applications. META expects its 2025 capital expenditures, including principal payments on finance leases, to be in the range of $70-$72 billion. A large part of this investment is made on servers, data centers and network infrastructure.
Meta Platforms will be scaling AI through massive computing power throughout 2026 and beyond. META’s one-gigawatt Prometheus cluster is under development, while Hyperion, which is scheduled to launch in 2028, is expected to be five gigawatts. The Zacks Consensus Estimate for META’s 2026 revenues and earnings indicates year-over-year growth of 18% and 31%, respectively. Estimates for 2026 earnings have been revised upward in the past seven days.
Image Source: Zacks Investment Research
Stock Price Performance and Valuation of SMCI & META
Shares of SMCI and META have plunged 37% and 14.3%, respectively, in the past six months.
Six-Month Performance Chart
Image Source: Zacks Investment Research
SMCI is trading at a forward 12-month Price to Sales ratio of 0.46X, which is lower than its median of 0.81X. META is trading at a forward sales multiple of 6.42X, lower than its median of 8.21X.
Forward 12-Month (P/S) Valuation Chart
Image Source: Zacks Investment Research
Conclusion: SMCI vs. META Stock
Although Super Micro Computer is rapidly growing due to the AI infrastructure demand, its rising working capital intensity, negative free cash flow, and slowing earnings revisions introduce near-term risk. On the other hand, Meta Platforms’ strategy of gaining from long-term AI hyperscale investments and near-term compute utilization while deepening its portfolio with improved chips, LLM models, upcoming AI clusters and rack systems gives it a varied edge over SMCI. META and SMCI carry a Zacks Rank #3 (Hold) each at present. You can see the complete list of today’s Zacks #1 Rank (Strong Buy) stocks here.
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SMCI vs. META: Which AI Infrastructure Stock Has an Edge Now?
Key Takeaways
Super Micro Computer (SMCI - Free Report) and Meta Platforms (META - Free Report) are two prominent AI enablers, playing slightly different roles in the AI infrastructure supply chain. While SMCI positions itself as the supplier of high-performance and energy-efficient servers, META is a hyperscale owner and consumer of AI compute for its family of apps.
Both SMCI and META are likely to gain from the growth of the AI market, which is projected to witness a CAGR 30.6% from 2025 to 2032, reaching a market size of $2407 billion by 2032, per a report by MarketsAndMarkets. Given this scenario, let's closely examine the fundamentals of the two companies, so investors can make an informed bet.
The Case for SMCI Stock
Super Micro Computer provides end-to-end AI rack-scale systems that integrate compute, networking, storage, and liquid cooling for AI data centers. SMCI uses the latest, most powerful and energy-efficient chips developed by NVIDIA and AMD in its servers, making them coveted among global AI data centers and high performance computing players. As new data centers are proliferating and existing ones are scaling up their capacity, the demand for SMCI’s systems is rising.
To enable its customers with rapid scaling, SMCI has introduced Data Center Building Block Solutions (DCBBS), which is modular and ideal for faster set-up. This product is also experiencing high traction among AI data centers and AI factories. The DCBBS incorporates SMCI’s rack-scale compute architecture for large-scale AI training, enterprise AI inference and training, visualization and design, content delivery and virtualization and AI edge.
SMCI’s upcoming facilities in the United States, Taiwan, Malaysia, the Netherlands, and the Middle East are explicitly designed for rack-level production, not just server assembly. SMCI has diversified its offerings by entering into client, edge and consumer AI markets. The company stands to benefit from its enterprise-scale expertise in AI-optimized servers, GPUs, and energy-efficient system design to deliver powerful yet compact solutions for PCs, edge AI, and embedded applications.
SMCI has launched Super AI Station, Supermicro SYS-542T-2R, Supermicro AI PC, Supermicro Edge AI Systems and Supermicro's Fanless Compact Edge System, challenging the existing players in this market for client, edge and consumer AI markets. With this business model at play, the company projects to achieve $36 billion in revenues in fiscal 2026, indicating a massive 64% year-over-year growth.
Nevertheless, to meet the demand, SMCI is expanding rapidly, causing inventory accumulation. SMCI’s first-quarter fiscal 2026 closing inventory was $5.7 billion, up from $4.7 billion in the previous quarter. This situation has spiked its cash conversion cycle from 96 days to 123 days. Negative free cash flow of $950 million for the first quarter of fiscal 2026 is another concern for the company. The Zacks Consensus Estimate for SMCI’s fiscal 2026 earnings shows a modest growth of 2.43%. The estimate has been revised downward in the past 60 days.
Image Source: Zacks Investment Research
The Case for META Stock
Meta Platforms builds, maintains and scales its own data center and technical infrastructure and uses third-party providers to supplement capacity. The company’s data center infrastructure is primarily internally driven to support its family of apps, which require AI training, inference and AI-based ranking systems to stay ahead of its competition. META’s family of apps investments were 79% of its total expenses in 2024, which included data centers and technical infrastructure expenses to develop apps and advertising services.
META has invested in the Meta Training and Inference Accelerator, which are custom-made chips for META’s AI workloads. In late 2024, META launched Catalina open-design, high-powered rack for AI workloads with integrated power, control, compute and interfaces. On the software application front, META is consolidating its smaller, task-specific models into larger, general models, improving performance and efficiency per unit of compute. The company also launched Llama 4, SAM 3, SAM 3D and other LLM models in 2025.
Per its third-quarter 2025 earnings call, Meta is fully focused on becoming a leading frontier AI lab and offering personal superintelligence worldwide. META is preparing for its superintelligence era by aggressively frontloading its building capacity, and in the meantime, using this extra compute power to improve the performance of its existing applications. META expects its 2025 capital expenditures, including principal payments on finance leases, to be in the range of $70-$72 billion. A large part of this investment is made on servers, data centers and network infrastructure.
Meta Platforms will be scaling AI through massive computing power throughout 2026 and beyond. META’s one-gigawatt Prometheus cluster is under development, while Hyperion, which is scheduled to launch in 2028, is expected to be five gigawatts. The Zacks Consensus Estimate for META’s 2026 revenues and earnings indicates year-over-year growth of 18% and 31%, respectively. Estimates for 2026 earnings have been revised upward in the past seven days.
Image Source: Zacks Investment Research
Stock Price Performance and Valuation of SMCI & META
Shares of SMCI and META have plunged 37% and 14.3%, respectively, in the past six months.
Six-Month Performance Chart
Image Source: Zacks Investment Research
SMCI is trading at a forward 12-month Price to Sales ratio of 0.46X, which is lower than its median of 0.81X. META is trading at a forward sales multiple of 6.42X, lower than its median of 8.21X.
Forward 12-Month (P/S) Valuation Chart
Image Source: Zacks Investment Research
Conclusion: SMCI vs. META Stock
Although Super Micro Computer is rapidly growing due to the AI infrastructure demand, its rising working capital intensity, negative free cash flow, and slowing earnings revisions introduce near-term risk. On the other hand, Meta Platforms’ strategy of gaining from long-term AI hyperscale investments and near-term compute utilization while deepening its portfolio with improved chips, LLM models, upcoming AI clusters and rack systems gives it a varied edge over SMCI. META and SMCI carry a Zacks Rank #3 (Hold) each at present. You can see the complete list of today’s Zacks #1 Rank (Strong Buy) stocks here.