B. Riley raised its Applied Materials price target to $790 from $550 on June 26 and kept a Buy rating, according to Insider Monkey and TipRanks/TheFly. The rationale centered on DRAM, advanced packaging, leading-edge foundry and logic exposure, and a multi-year semiconductor equipment investment cycle tied partly to AI demand. For ML infrastructure teams, this is not a product update, but it reinforces a market signal: AI capacity growth depends on upstream wafer-fab equipment, packaging intensity, and memory investment as much as on GPU vendors.
The useful AI angle is upstream capacity. Applied Materials does not sell training clusters to developers, but its tools sit in the semiconductor equipment layer that determines how much advanced logic, DRAM, and packaging capacity the AI supply chain can support.
What happened
Insider Monkey reported that B. Riley raised its Applied Materials price target to $790 from $550 on June 26, 2026 and maintained a Buy rating. TipRanks/TheFly reported the same target change and said B. Riley cited Applied Materials' DRAM and Advanced Packaging Master Class as evidence of a larger-than-expected long-term opportunity.
Technical context
Advanced packaging and DRAM capacity are increasingly important to AI infrastructure because model training and inference systems depend on high-bandwidth memory, dense interconnects, and leading-edge foundry and logic process capability. A price-target increase is only a market view, but the supporting thesis points to the physical manufacturing constraints behind AI compute expansion.
For practitioners
Teams planning AI infrastructure should watch semiconductor equipment and packaging signals as upstream indicators of future capacity and cost. When equipment demand, memory pricing, and advanced packaging constraints all rise together, cloud pricing and hardware lead times can shift even before end customers see shortages.
Key Points #
- 1B. Riley raised Applied Materials target to $790 from $550 while maintaining a Buy rating.
- 2The rationale centered on DRAM, advanced packaging, leading-edge logic, and a multi-year equipment cycle thesis.
- 3AI infrastructure teams should treat semiconductor equipment demand as an upstream capacity and cost signal.
Scoring Rationale #
This is a solid AI-infrastructure market signal because it concerns equipment, memory, and advanced packaging capacity. It remains moderate impact because the trigger is an analyst target update rather than a new manufacturing milestone or reported earnings event.
Sources #
Public references used for this report. Practice with real FinTech & Trading data
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