Behold, Intel plans a 480GB GPU, a video card with more memory than the average laptop SSD has storage but of course it's for AI, and curiously, it will use LPPDR5X, not even GDDR7

Date:
Sun, 18 Oct 2026 20:05:00 +0000

Description:
The Intel 480GB GPU combines 1.5TB/s bandwidth, 1.3 petaflops FP8
performance, and 350W power consumption, although pricing and availability remain undisclosed.

FULL STORY ======================================================================Copy link Facebook X Whatsapp Reddit Pinterest Flipboard Threads Email Share this article 0 Join the conversation Follow us Add us as a preferred source on Google Newsletter Subscribe to our newsletter Intel's GPU D-series sets a new GPU memory record with 480GB of LPDDR5X Intel chose LPDDR5X instead of GDDR7 for its high-capacity AI accelerator The D-series supports models containing up to 300 billion parameters At the recent Open Compute Project Global
Summit, Intel unveiled a graphics processor with up to 480GB of memory, an unusually large capacity designed for demanding AI inference workloads.

The GPU , called Intel GPU D-series and previously known by its Crescent Island codename, also hosts specialized computing hardware. The Intel
D-series has now dethroned Nvidia 's Blackwell Ultra B300, which offers 288GB of HBM3e memory, as the data center GPU with the highest memory capacity. Latest Videos From TechRadar Watch full video here: Intel prioritizes memory capacity Rather than using GDDR7 memory associated with modern graphics
cards, Intel has chosen LPDDR5X, a memory technology commonly found in
laptops and other power-conscious devices.

The configuration suggests that Intel is prioritizing memory capacity and power efficiency for AI inference instead of designing a conventional gaming graphics card. You may like Nvidia uses a memory 'sandwich' technique to cram 84GB GDDR7 memory on RTX Pro 5500 Blackwell GPU weird 416-bit memory bus leaves me puzzled, though Chinese vendor debuts world's first AMD Ryzen AI Max+ Pro 495 laptop, but 192GB LPDDR5X-8533 for gaming? Really?? This AI SSD tech makes 8 RTX 5090s perform like 46 GPUs in inference

Intel says the accelerator can support large language models containing up to 300 billion parameters on one card, while an eight-GPU system can accommodate models exceeding one trillion parameters.

These capabilities are intended for lengthy prompts, simultaneous inference requests, enterprise AI services, and robotics applications requiring responsive processing. Are you a pro? Subscribe to our newsletter Sign up to the TechRadar Pro newsletter to get all the top news, opinion, features and guidance your business needs to succeed! Contact me with news and offers from other Future brands Receive email from us on behalf of our trusted partners
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Inference is becoming the defining AI workload, and enterprises need infrastructure that delivers the right performance at the right cost, said Anil Nanduri, vice president, AI Products & GTM, Intel Data Center Group.

With Intel GPU D-series, we're focused on making high-capacity inference practical to deploy and economical to scale.

The 480GB capacity is particularly relevant when AI systems must keep substantial model weights and associated data accessible during inference. What to read next Thunderobot just launched a laptop that uses a special RAM-like SSD to boost AI performance AI Master M7000 packs Ryzen AI Max+ 395 with 64GB RAM, runs 120B MoE models HP debuts $7,449 Ryzen AI Max+ PRO 495 laptop ZBook Ultra G3a has 192GB RAM, 512GB SSD, and can handle up to 300B parameters Startup swaps costly AI GPUs for Arm cores and up to 128TB of 'cheap' LPDDR6 RAM instead of expensive HBM to smash through the memory wall

However, memory capacity alone does not establish how quickly a GPU will
serve requests, since performance also depends on bandwidth, computing resources, software, and workload characteristics.

Intel rates the D-series at 1.3 petaflops for FP8 computation, a numerical format commonly used to accelerate AI operations while reducing memory requirements compared with higher-precision formats.

Its 1.5TB/s memory bandwidth provides a separate measure of how quickly data can move between memory and the processor. Intel wants the accelerator to fit existing data centers The company specifies a 350W power envelope and a standard PCIe form factor, alongside air cooling and software compatibility across its GPU platforms.

These characteristics are intended to simplify deployment in existing data centers without requiring specialized cooling arrangements or entirely new rack infrastructure.

Intel also plans to connect the accelerator with its Xeon processors,
allowing CPUs to coordinate tasks, manage data movement, and handle workloads that do not require GPU acceleration.

This approach addresses AI systems increasingly built around multiple stages, including retrieval, reasoning, orchestration, external tools, and execution.

Open models are expanding the options enterprises have for deploying AI, said Nicolas Dub, corporate vice president, Data Center Systems and Solutions Group, Intel.

To realize their full potential, organizations need infrastructure that can match different workloads with the right intelligence, right compute
resources and right economics. That's what we mean by 'put every prompt in
its place.

As of the time of writing, Intel has not revealed the public retail price or
a specific general-availability date for the GPU D-series. Follow TechRadar
on Google News and add us as a preferred source to get our expert news, reviews, and opinion in your feeds.



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