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Today β€” 10 April 2026Main stream

Intel Arc Pro B70 Quad-GPU Setup Reportedly Consumes Up To 720W In Inference Workloads

9 April 2026 at 15:48

Big Battlemage Is Here - Intel Unveils Arc Pro B70 & B65 GPUs, Up To 32 GB Memory & 367 TOPS For AI 1

With limited reviews available, you will hardly hear about the Arc Pro B70's performance. Here's a sneak peek into the analysis by Hardware Luxx. Hardware Luxx Intel Arc Pro B70 Review Reveals GPU's Performance Against Its Competitors Intel's flagship workstation Big Battlemage GPUs were released roughly two weeks ago, but since then, we have hardly seen any reviews for the Arc Pro B65 and the Arc Pro B70. It appears that the GPUs don't have good availability, and similar to what we heard about the Arc Pro B60 last year, both the newer GPUs may not be that abundant in […]

Read full article at https://wccftech.com/intel-arc-pro-b70-quad-gpu-setup-reportedly-consumes-up-to-720w-in-inference-workloads/

Intel Arc GPUs can finally boot up and play 'Crimson Desert' β€” but you'll probably want to wait for official support

Intel's latest GPU driver is capable of booting Crimson Desert and can reportedly run at nearly 60 FPS at ultra settings on an Arc B580. But the game suffers from occasional crashing and visual artifacts.

Yesterday β€” 9 April 2026Main stream
Before yesterdayMain stream

Apple approves drivers that let AMD and Nvidia eGPUs run on Mac β€” software designed for AI, though, and not built for gaming

The company behind the tiny box AI accelerator says that its macOS driver for Nvidia eGPUs has just been signed by Apple, making it a legitimate software for Macs and no longer needs workarounds to work with the device.

Nvidia AI tech claims to slash gaming GPU memory usage by 85% with zero quality loss β€” Neural Texture Compression demo reveals stunning visual parity between 6.5GB of VRAM and 970MB

Nvidia has just demoed its Neural Texture Compression technique again at a GTC talk, where it showed VRAM usage dropping from 6.5 GB to just 970 MB in a scene. NTC uses a neural network to decompress textures instead of standard block-based compression, reducing texture size and VRAM usage while also improving final image quality.

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