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VOOZH | about |
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VOOZH | about |
Allan Witt is the co-founder and Editor-in-Chief of Hardware-Corner.net. Computers and the web have fascinated him since childhood. In 2011, he began training as an IT specialist at a mid-sized company while launching a tech blog on the side—quickly discovering a passion for writing about hardware and technology.
After completing his training, Allan worked as a system administrator for two years. Alongside that, he started building and upgrading custom gaming PCs at a local hardware shop. What began as a part-time project grew into a full-time career. Today, his work also focuses on building and optimizing PC systems for local AI and LLM workloads, combining hands-on experience with a passion for making complex tech easy to understand.
Apr. 27, 2025 / LLM Hardware News
The landscape for local LLM inference hardware has just become more interesting with recent developments in NVIDIA’s memory supply chain. SK Hynix has joined Samsung as a GDDR7 memory supplier for the GeForce RTX 50 series, with initial implementations appearing on RTX 5070 Ti cards in the Chinese market. For the local LLM enthusiast community,...
Apr. 21, 2025 / LLM Hardware News
Chinese manufacturer FAVM has announced FX-EX9, a compact 2-liter Mini-PC powered by AMD’s Ryzen AI MAX+ 395 “Strix Halo” processor, potentially offering new options for enthusiasts running quantized large language models locally.
Apr. 19, 2025 / LLM Hardware News
What makes QAT particularly impressive is its ability to maintain model quality despite the dramatic reduction in precision. According to Google, they’ve reduced the perplexity drop by 54% (using llama.cpp perplexity evaluation) when quantizing down to Q4_0.
Apr. 17, 2025 / LLM Hardware News
In a significant move for the local LLM inference community, Intel has announced that it’s open sourcing AI Playground, its versatile platform for generative AI that was previously exclusive to Intel hardware. This development comes at a critical time as AMD also enhances its generative AI capabilities through collaborations with Tensorstack and Stability.AI. Arc GPUs...
Apr. 16, 2025 / LLM Hardware News
The much-anticipated NVIDIA RTX 5060 Ti has finally hit retail shelves, with the 16GB model now available from major retailers like Newegg and Best Buy. Initial pricing has settled between $470-$570 for most standard models, representing a modest 10-23% premium over the stated $429 MSRP. While premium models like the ASUS TUF Gaming OC edition...
Apr. 15, 2025 / LLM Hardware News
NVIDIA has officially unveiled the RTX 5060 Ti with 16GB of GDDR7 memory at $429, positioning it as a compelling option for local LLM enthusiasts. At this price point, the card not only offers excellent standalone value but opens up an even more enticing possibility: a dual-GPU configuration that rivals high-end solutions at a fraction...
Apr. 15, 2025 / LLM Hardware News
In just two days, NVIDIA is set to launch their RTX 5060 Ti, and recently leaked specs suggest this card could become the go-to option for budget-conscious LLM enthusiasts looking to run impressive models locally. With the rising prices and dwindling availability of used RTX 3090s, this new mid-tier offering presents an intriguing alternative for...
Apr. 7, 2025 / LLM Hardware News
The landscape of local large language model (LLM) inference is evolving at a breakneck pace. For enthusiasts building dedicated systems, maximizing performance-per-dollar while navigating the ever-present VRAM ceiling is a constant challenge.
Apr. 7, 2025 / LLM Hardware News
With VRAM capacities breaching the 24GB ceiling common on consumer GPUs, Tenstorrent is making a bid for users running increasingly large models locally. But the critical question for the DIY AI community remains.
Apr. 6, 2025 / LLM Hardware News
We’ll break down what hardware you need for Llama 4, using both MLX (Apple Silicon) and GGUF (Apple Silicon/PC) backends, with a focus on performance-per-dollar, memory constraints, and hardware availability for price-conscious builders.
Apr. 4, 2025 / LLM Hardware News
G.Skill just dropped an announcement that should catch the eye of every LLM tinkerer: two new high-end DDR5 kits, one at DDR5-8000 with 128 GB capacity, and another at DDR5-9000 with 64 GB capacity.
Apr. 1, 2025 / LLM Hardware News
Recent benchmarks show that a dual RTX 5090 setup outperforms the H100 in sustained output token generation, making it an ideal choice for those seeking the best possible performance.
Mar. 31, 2025 / LLM Hardware News
A recent test of DeepSeek V3 (671B parameters, 37B active MoE) on a dual-EPYC setup with 768GB DDR5-5600MHz memory reveals interesting performance insights. We’ll break down the results and compare them to alternatives.
Mar. 30, 2025 / LLM Hardware News
GMKtec has officially priced its EVO-X2 SFF/Mini-PC at ~$2,000, positioning it as a potential option for AI enthusiasts looking to run large language models (LLMs) at home.
Mar. 28, 2025 / LLM Hardware News
Early tests on a laptop equipped with a 135W RTX 5090 GPU, revealing significant performance gains over the RTX 4090 Mobile. Given that this is the first consumer laptop GPU with 24GB of VRAM, it opens new possibilities for running large-scale quantized LLMs locally.
Mar. 27, 2025 / LLM Hardware News
Hardware modding scene in China continues to innovate. Reports showcase a compelling modification: an NVIDIA GeForce RTX 4090 equipped with a staggering 48GB of GDDR6X memory, double the stock configuration.
Mar. 27, 2025 / LLM Hardware News
We took a closer look at how the top-tier M3 Ultra fares when running the colossal DeepSeek V3 671B parameter model using the popular llama.cpp inference engine. The results paint a picture of impressive capability tempered by significant performance considerations.
Mar. 26, 2025 / LLM Hardware News
This analysis breaks down GeForce GPUs based on their ability to run an 8B model in 4-bit quantization (Q4_K_M) while considering MSRP vs. retail pricing in March 2025. Our key metric is tokens per second per dollar.
Mar. 26, 2025 / LLM Hardware News
While Nvidia’s official materials emphasize its gaming-focused features, we dug deeper into its actual implementation. Surprisingly, G-Assist is powered by Llama 3.1 8B and runs locally using Llama.cpp.
Mar. 26, 2025 / LLM Hardware News
Today, we're diving deep into G-Assist’s technical implementation, its model, and, most importantly, its impact on VRAM usage during gaming sessions.