Nvidia (NVDA) shares remain in focus this week after the semiconductor behemoth confirmed it’s spending $20 billion to acquire Groq’s assets and talents. Founded in 2016, this artificial intelligence (AI) startup based out of Mountain View, California specialize in high-bandwidth, low-latency architectures. More News from Barchart At the time of writing, Nvidia stock is up roughly 120% versus its year-to-date low set in early April. www.barchart.com Mizuho Explains Why Groq Deal Is Bullish for Nvidia ...

Core Viewpoint - Wells Fargo maintains an Overweight rating and a price target of $265 on NVIDIA following the clarification of its relationship with AI hardware firm Groq [1] Group 1: Acquisition and Licensing Agreement - Speculation regarding NVIDIA's potential $20 billion acquisition of Groq was addressed after Groq announced a non-exclusive licensing agreement with NVIDIA [2] - The agreement is viewed as an acqui-hire, with key Groq personnel joining NVIDIA to enhance global AI inference capabilities [2] Group 2: Strategic Focus and Technology Insights - The strategic focus of the agreement is on latency-sensitive and deterministic AI inference, granting NVIDIA access to Groq's specialized hardware and compiler software [3] - The deal raises questions about NVIDIA's perspective on high-bandwidth memory, as Groq's LPUs utilize on-chip SRAM, which can outperform HBM by up to 10 times [3] Group 3: Comparisons and Future Considerations - The Groq agreement is compared to NVIDIA's previous $900 million acqui-hire of Enfabrica, which targeted memory architecture advancements [4] - Questions arise regarding the potential integration of NVIDIA's NVLink C2C interconnect with Groq's architecture to improve inference-optimized systems [4] - Considerations include Groq's positioning relative to NVIDIA's Rubin CPX platform, designed for large-context inference workloads with 128GB of GDDR7 memory expected to be available in late 2026 [4]

Broad-market leaders often emerge after a single catalytic development reshapes an industry’s competitive map. Sometimes those catalysts are incremental, and sometimes they’re seismic, forcing investors to reassess positioning. Nvidia (NVDA) just experienced the latter as it announced it would license AI inference technology from startup Groq (a non-exclusive agreement). Under this deal, Groq’s founder, Jonathan Ross, president Sunny Madra, and other key engineers will join Nvidia to help advance Groq’s l ...

Accessible version Groq LPU complement NVDA core GPU platform Think of GPU as a general-purpose platform, while Groq LPU as specialized, ASIC-like chips for fast and predictable AI inference token generation. (As reference Groq founder/CEO Jonathan Ross was also the key inventor of Google TPU custom chip). We envision future NVDA platforms where GPU and LPU co-exist in a rack, connected seamlessly with NVDA's NVLInk networking fabric. Groq's LPU employ a large amount (hundreds of MB) of fast on-chip SRAM me ...

Now, Mackenzie Sagalos has more in today's tech check. And Mackenzie, I I sort of stopped short when I was reading about this. Maybe you can help explain because he called this a licensing deal, but then it said, I believe, if I'm not mistaken, that the CEO of Gro is going to go work for Nvidia and that it's non-exclusive.I'm like, what is this. An acquisition or what is this. >> It's not an acquisition.They've been very specific in saying that. But this Grock deal came together in just a few days. in the s ...

on 25-Dec-2025 25 December 2025 U.S. Semiconductors NVIDIA (NVDA): Can you Groq it? Stacy A. Rasgon, Ph.D. +1 213 559 5917 stacy.rasgon@bernsteinsg.com Alrick Shaw +1 917 344 8454 alrick.shaw@bernsteinsg.com Arpad von Nemes +1 917 344 8461 arpad.vonnemes@bernsteinsg.com On Christmas eve (joy) CNBC reported that NVIDIA was buying AI silicon startup Groq for $20B in cash. Subsequently, Groq announced that the company had "entered into a non-exclusive licensing agreement with Nvidia" for Groq's inference techn ...

Core Insights - Nvidia has entered into a licensing agreement with Groq to utilize its chip technology and has hired Groq's CEO, a former Google executive [1][3] - Groq specializes in inference technology for AI, an area where Nvidia faces increasing competition from both established companies like AMD and startups such as Groq and Cerebras Systems [2] - Groq's valuation has surged to $6.9 billion from $2.8 billion in August last year, following a $750 million funding round in September [4][8] Company Developments - The licensing agreement with Nvidia is described as "non-exclusive," allowing Groq to continue operating independently with its current leadership [3][4] - Groq's technology utilizes on-chip memory (SRAM) instead of external high-bandwidth memory chips, which helps mitigate the memory constraints affecting the global chip industry [6] - Groq's primary competitor in this technology space is Cerebras Systems, which is also planning to go public soon [7] Market Context - Nvidia's CEO has emphasized the company's strategy to maintain its leadership position as the AI market transitions from training to inference [5][7] - The competitive landscape for inference technology is intensifying, with both traditional and new players vying for market share [2]

J P M O R G A N Asia Pacific Equity Research 14 December 2025 Global Memory Market 2026 outlook: Disinflation continues with AI inference pick-up and supply constraints Technology - Semiconductors Jay Kwon AC (82-2) 758-5725 jay.h.kwon@jpmorgan.com J.P. Morgan Securities (Far East) Limited, Seoul Branch Sangsik Lee (82-2) 758 5146 sangsik.lee@jpmorgan.com J.P. Morgan Securities (Far East) Limited, Seoul Branch Neelay Y Kamath (91-22) 6157 3764 neelay.kamath@jpmchase.com J.P. Morgan India Private Limited Har ...

Valued at a market cap of $12.4 billion, Akamai Technologies, Inc. (AKAM) is a prominent provider of cloud computing, cybersecurity, and content delivery network services. Headquartered in Cambridge, Massachusetts, the company operates a globally distributed edge platform that helps enterprises deliver faster, more secure, and more reliable digital experiences to users worldwide. Companies valued at $10 billion or more are typically classified as “large-cap stocks,” and AKAM fits the label perfectly, wit ...

In the past, AI demand has primarily focused on training workloads, particularly for frontier models. While leading tech companies continue pouring resources into building ever-larger AI models, they are also reallocating more investment toward inference. Inference is the stage where trained AI models process new data to generate insights, make predictions or support decision-making. While training a model is essentially a one-time expense, prompting a model (inference) produces tokens, each of which carrie ...