Google's free Gemma 4 model runs on hardware you probably already own
…Apple Silicon can run E4B on 8GB of RAM, or 26B MoE on 16GB (though more comfortable at 32GB), and 64GB of RAM will happily run the 31B Dense model. It won…
…Apple Silicon can run E4B on 8GB of RAM, or 26B MoE on 16GB (though more comfortable at 32GB), and 64GB of RAM will happily run the 31B Dense model. It won…
…rival or exceed systems with discrete GPUs, making Apple laptops surprisingly competitive for local AI. The correct answer is unified memory. Apple Silicon doesn't support CUDA (that's NVIDIA-specific), but…
…rival or exceed systems with discrete GPUs, making Apple laptops surprisingly competitive for local AI. The correct answer is unified memory. Apple Silicon doesn't support CUDA (that's NVIDIA-specific), but…
…That’s when I found Choragus as a worthy replacement for that to make it work on my Apple Silicon-based MacBook Air. After I downloaded and installed it, there was no…
…What problem is RTX Spark solving, and for whom? What does the RTX Spark promise? The same thing AI PCs have promised, with much more powerful silicon The RTX Spark is one…
…AMD has revealed that it's bringing its FidelityFX Super Resolution 4.1 (FSR) AI upscaling technology to its older graphics cards. In a post on Twitter , Jack Huynh, AMD's Senior…
…bringing local AI to hardware that most users can afford. Related My RTX 5090 can't keep up with Apple Silicon on the biggest local LLMs, and I hate to admit it…
…Gemini's on-device and cloud capabilities are quite strong as far as the consumer AI field goes right now, and Google's partnership powering the next version of Siri suggests Apple…
…level Same silicon, different wrapper When Nvidia announced the RTX Spark at Computex, it framed the chip as a consumer Windows-on-Arm platform for creators, developers, and AI enthusiasts. At the…
…rival or exceed systems with discrete GPUs, making Apple laptops surprisingly competitive for local AI. The correct answer is unified memory. Apple Silicon doesn't support CUDA (that's NVIDIA-specific), but…