Hardware

The memory market is experiencing unprecedented price volatility in late 2025, with RAM prices surging dramatically across all segments.

Let’s compare prices for top-level consumer GPUs, that are suitable for LLMs in particular and AI in general. Specifically I’m looking at RTX-5080 and RTX-5090 prices.

The democratization of AI is here. With open-source LLMs like Llama 3, Mixtral, and Qwen now rivaling proprietary models, teams can build powerful AI infrastructure using consumer hardware - slashing costs while maintaining complete control over data privacy and deployment.

Docker Model Runner is Docker’s official tool for running AI models locally, but enabling NVidia GPU acceleration in Docker Model Runner requires specific configuration.

I dug up some interesting performance tests of GPT-OSS 120b running on Ollama across three different platforms: NVIDIA DGX Spark, Mac Studio, and RTX 4080. The GPT-OSS 120b model from the Ollama library weighs in at 65GB, which means it doesn’t fit into the 16GB VRAM of an RTX 4080 (or the newer RTX 5080).

Docker Model Runner (DMR) is Docker’s official solution for running AI models locally, introduced in April 2025. This cheatsheet provides a quick reference for all essential commands, configurations, and best practices.

In today’s computing landscape, virtualization has become essential for development, testing, and running multiple operating systems. For Linux users seeking a simple, intuitive way to manage virtual machines, GNOME Boxes stands out as a lightweight and user-friendly option that prioritizes ease of use without sacrificing functionality.

The future of AI isn’t just about smarter models - it’s about smarter silicon. Specialized hardware for LLM inference is driving a revolution similar to Bitcoin mining’s shift to ASICs.

NVIDIA DGX Spark is real, on sale Oct 15, 2025, and targeted at CUDA developers needing local LLM work with an integrated NVIDIA AI stack. US MSRP $3,999; UK/DE/JP retail is higher due to VAT and channel. AUD/KRW public sticker prices are not yet widely posted.

Let’s compare prices for top-level consumer GPUs, that are suitable for LLMs in particular and AI in general. Specifically I’m looking at RTX-5080 and RTX-5090 prices. They have slightly dropped.

GPU load monitoring applications: nvidia-smi vs nvtop vs nvitop vs KDE plasma systemmonitor.

Nvidia is about to release NVIDIA DGX Spark - little AI supercomputer on blackwell architecture with 128+GB unified RAM and 1 PFLOPS AI performance. Nice device to run LLMs.

Let’s compare prices for top-level consumer GPUs, that are suitable for LLMs in particular and AI overall. Specifically have a look at RTX 5080 and RTX 5090 prices. They have slighty dropped.

Just 3 month ago we didn’t see RTX 5090 in shops, and now here they are, but the prices are slightly higher then MRSP. Let’s compare the cheapest prices for RTX 5080 and RTX 5090 in Australia and see how it goes.

Top Automated system for some awesome job.

How PCIe Lanes Affect LLM Performance? Depending on the task. For training and multi-gpu inferrence - perdormance drop is significant.