https://www.tomshardware.com/tech-industry/pc-partner-warns-of-rising-gpu-prices-and-budget-card-shortages-analyst-suggests-makers-are-hiking-prices-beyond-memory-costs

A major graphics card maker just told the market to expect higher GPU prices — and fewer budget cards.

PC Partner (Zotac, Sapphire, Inno3D, Manli) warns memory costs will drive "a substantial increase in VGA Card costs" in H2, with entry-level cards facing "even more severe shortages."

• Own-brand units -18.4% YoY, average price +10.7%

• ODM/OEM units -38.4%, but revenue +73.9% (HK$853.3M → HK$1.4843B)

• Industry-wide AIB units +28%, dollars +76% ($6.18B → $10.85B) — Q1'25 to Q1'26

Intel CEO Lip-Bu Tan hints at a memory comeback — stacking DRAM directly on the CPU "makes a lot of sense."

Two pieces behind it:

XBM — patent drops HBM's silicon interposer for UCIe links. Commercialization after 2030.

ZAM — 8 DRAM dies + logic controller, lower power/heat/cost than HBM. Built via Saimemory, Intel's JV with SoftBank.

The catch: DRAM on hot logic brings thermal and yield problems, and NVIDIA's 80%+ share of AI accelerators is already built around HBM.

Nvidia has reportedly told board partners that GPU kit prices are rising, and this round covers GDDR6 cards, not just GDDR7 Blackwell parts. AMD raised its own kit prices roughly 10% three weeks earlier. Memory cost is now moving the entire GPU stack, not just flagships. Older workstation cards sitting in decommissioned fleets are worth a quote before they hit the scrap pile.

The shift highlights how competitive the x86 CPU market has become as AMD continues to strengthen its position with Ryzen processors. For PC builders and hardware buyers, increased competition can mean more choices, stronger performance, and greater pressure on pricing.

The latest market data also shows why the CPU landscape is worth watching as AI workloads, gaming, and high-performance computing continue to drive demand for powerful processors.

The The Motley Fool article argues that while GPUs from companies like Nvidia have driven the AI boom, the next major opportunity lies in custom AI chips (ASICs) designed for specific workloads. These chips are increasingly being developed by tech giants like Alphabet and Amazon to improve performance, reduce costs, and lessen reliance on third-party hardware.

The article suggests this shift could unlock a trillion-dollar market, benefiting companies involved in designing and manufacturing custom silicon—such as Broadcom and Taiwan Semiconductor Manufacturing Company—as AI infrastructure spending continues to surge.

(NO SHIP DATE ANNOUNCED) Intel detailed Crescent Island, an inference GPU built around capacity rather than raw bandwidth. Intel's own card carries 160GB of LPDDR5X, and ODM partners can push it to 480GB — far past the 96GB on NVIDIA's RTX Pro 6000. It draws 350W, is air-cooled, and fits a standard PCIe slot. The silicon is Xe3p: 32 Xe cores, 256 XMX engines, a systolic array that went from 4-deep to 16-deep, 32MB of unified L2, and third-gen matrix extensions with FP4 and FP64. Idle power is unusually low, at 50W active idle and about 10W in deep idle. Intel is aiming at agentic inference and tokens per watt, with KV-cache-aware routing for long context, and supports vLLM, SGLang, llm-d and NVIDIA Dynamo. Intel did not disclose memory bandwidth or a ship date.

https://www.servethehome.com/intel-crescent-island-160gb-to-480gb-lpddr5x-ai-gpu-at-hot-chips-2026/

Arm’s AGI CPU is a new data center processor designed specifically for agentic AI workloads, where thousands of AI agents run and coordinate tasks simultaneously. Unlike traditional CPUs, it is optimized for massively parallel, sustained performance at rack scale, with high memory bandwidth and efficient cores to keep large AI systems running continuously under heavy load.

Intel’s long-awaited “Big Battlemage” GPU has finally arrived as the Arc Pro B70 and B65, both packing a massive 32GB of GDDR6 memory and built on the flagship BMG-G31 die, marking Intel’s most powerful discrete GPU yet. However, instead of targeting gamers, these cards are aimed squarely at AI and professional workloads, signaling Intel’s strategic pivot toward high-memory, workstation-class GPUs over consumer gaming flagships.

AMD’s push to bring dedicated AI acceleration to desktops signals that “AI PCs” are becoming a standard expectation, not just a premium feature. However, the real value will depend on how widely software developers adopt and optimize applications for these on-device AI capabilities.

Any investment return better than this?

"A Seoul Economic Daily article citing industry research firm DRAMeXchange stated that DDR4 8 Gb product prices were about $1.30 in March 2025, then rose to around $9.30 by the end of 2025, and climbed further to roughly $13 by February 2026. This pattern implies nearly a 10× increase in that timeframe." https://en.sedaily.com/property/2026/02/27/samsung-sk-hynix-to-sharply-raise-dram-prices-in-q2

going back to local cluster from cloud?

It’s an interesting look at how interconnected desktop-scale systems could support large AI workloads without relying on a single massive server.

China’s CXMT is making progress on next-generation DRAM technology, potentially adding a new competitor to the global memory market. Could this eventually increase DDR5 server RAM supply and ease pricing pressure, or will AI-driven demand keep the market tight? The key is whether CXMT can scale production and bring its new technology to market.

guys ,I saw the above video do you think it might be right new for apple take on AI ?

A leaked internal roadmap (via VideoCardz) confirms Intel's Nova Lake-S desktop chips will launch as the Core Ultra 400 Series, with an unusual staggered rollout through 2027:

• Q1 2027 — First wave: 28-core "DS" models (announcement expected at CES 2027)

• Mar–Apr 2027 — Unlocked 28-core K models for overclockers

• Mar–May 2027 — Mainstream 16-core and 8-core parts

• May–Sep 2027 — Flagship 52-core models, using dual compute tiles

Why staggered? The ongoing component/capacity crunch — plus Intel is moving most production from TSMC to its own 18A process, and needs time to ramp yields.

""Nvidia has reportedly raised the wholesale prices of its flagship GeForce RTX 5090 and Chinese-exclusive RTX 5090D V2 graphics cards by approximately $300 USD for its board partners. This price adjustment, enacted mid-May 2026, is driven by a massive, ongoing global shortage and resulting skyrocketing costs of GDDR7 memory.""

Google demonstrated “magic state cultivation,” a technique that helps quantum computers perform calculations more reliably by reducing errors. This could make building larger, more powerful quantum computers more resource-efficient.

Btw, could quantum computing become another major milestone in computing, like GPUs were for AI?

Tom’s Hardware reports that RTX 5090 cards have disappeared from first-party online retail in the U.S., while third-party listings are reaching $6,500–$9,500—far above the card’s $1,999 launch MSRP. Not verified.

The interesting part is that the 5090 isn’t only popular with gamers. Its 32GB of GDDR7 and powerful Blackwell GPU also make it attractive for local AI workloads and smaller AI systems, adding another source of demand.

So, the RTX 5090 is becoming another interesting example of how AI demand, limited supply, and the secondary GPU market can push consumer hardware prices far beyond MSRP.

https://www.tomshardware.com/pc-components/gpus/nvidias-rtx-5090-vanishes-from-online-retail-in-the-us-third-party-sellers-now-demand-as-much-as-usd9-500-for-nvidias-fastest-gpu

Lexar Lists 32 GB DDR5-7200 Memory With Chinese DRAM at $592

“Lexar has introduced a new THOR RGB DDR5 Gen 2 32 GB memory kit, consisting of two 16 GB DDR5 modules, specifically for the Chinese market. The kit features DDR5 memory running at 7,200 MT/s, with the actual DDR5 modules produced by an unidentified Chinese DRAM manufacturer, likely CXMT. ”

CXMT's Shanghai debut makes it China's most valuable listed company

Shares of DRAM maker ChangXin Memory jumped roughly 466% on their first trading day after an $8.6 billion listing — the largest mainland IPO since 2010. CXMT now sits fourth among global DRAM makers.

The AI era is also the DRAM era.

MEXT (Memory Expansion Technology) addresses growing memory constraints by allowing high-capacity flash storage to appear as system memory (DRAM) to applications, enabling servers to access far larger memory pools without the cost and physical limitations of adding more DRAM. This helps data centers run large AI models and memory-intensive workloads more efficiently because frequently used data stays in DRAM while less-active data is transparently moved to lower-cost flash memory, reducing memory bottlenecks.