#GPU workstation
63 related articles
Tutorials·3 min
Running AI Models on a P106 Mining GPU: Build a Local AI Workstation for Under $10
Build a local AI workstation with a P106 mining GPU for under $10. Run Live Portrait and other AI models locally with full privacy, zero marginal cost, and incredible value.
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·4 min
Laguna S 2.1 Deep Dive: Hands-On Local Deployment of a 118B Parameter Coding Model
In-depth review of Poolside's Laguna S 2.1 open-source coding model: MoE architecture, RL training, DGX Spark local deployment, and real-world agentic coding tests with 8B active parameters.
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·3 min
Monocular RGB Human Mesh Reconstruction: Real-Time Motion Capture at 18 FPS with Rust + CUDA
Deep dive into a real-time 3D human mesh reconstruction project using a single RGB camera, built with Rust, Candle, and CUDA, achieving 55ms/frame on RTX 5080. Exploring its architecture, Metal porting plans, and applications in VTuber, AR/VR, and sports analysis.
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·3 min
Monocular RGB Human Mesh Reconstruction: Real-Time Motion Capture at 18 FPS with Rust + CUDA
A deep dive into a real-time 3D human mesh reconstruction project using a single RGB camera, built with Rust, Candle, and CUDA, achieving 55ms/frame on an RTX 5080.
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·3 min
After 6 Billion Tokens, Here's What I've Learned About AI Agents
A power user who consumed over 6 billion Tokens shares real insights on AI Agents, exploring spending money, investing time, and managing life changes with AI.
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·3 min
Self-Hosting Hardware Upgrade Guide: From an Old NUC to a Game Server and Beyond
A detailed guide to self-hosting hardware upgrades: analyzing NUC bottlenecks, comparing used enterprise Mini PCs and ITX builds for Jellyfin, Immich, and Minecraft servers.
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·3 min
Self-Hosting Hardware Upgrade Guide: From an Old NUC to a Game Server and Beyond
A detailed guide to self-hosting hardware upgrades: analyzing NUC performance bottlenecks, comparing used enterprise Mini PCs and custom ITX builds for Jellyfin, Immich, and Minecraft servers.
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·3 min
After 6 Billion Tokens, Here's What I've Learned About AI Agents
A power user who consumed over 6 billion Tokens shares hard-won insights on AI Agents: the real costs, the time investment, and maintaining healthy boundaries.
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·2 min
RX 9060 XT vs RTX 5060 Ti: Which GPU to Pick for Local AI?
RX 9060 XT vs RTX 5060 Ti — both 16GB VRAM, but which is better for local AI? We compare CUDA ecosystem, ROCm compatibility, LLM inference, and real-world usability.
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·2 min
RX 9060 XT vs RTX 5060 Ti: How to Choose a GPU for Local AI
RX 9060 XT vs RTX 5060 Ti both offer 16GB VRAM — which is better for local AI inference? A full comparison of CUDA ecosystem, ROCm compatibility, LLM performance, and real-world usability.
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·3 min
Sebastian Lague's Custom Graphics Library: A Complete Breakdown of Building a Renderer from Scratch
Deep dive into Sebastian Lague's experiment building a graphics library from scratch, covering rasterization, depth buffering, texture mapping, and the educational value of software renderers.
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·3 min
Laguna S 2.1: The Open-Source Coding Model That's 14x Smaller Yet Stronger
Poolside releases Laguna S 2.1, an open-source agentic coding model: 118B total params with only 8B active, scoring 40.4% on DeepSWE — ~4.5x DeepSeek V4 Pro Max. Supports 1M-token context, deployable on a single workstation.
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·6 min
How the Creator of Redis Squeezed a 284B-Parameter DeepSeek into an Ordinary Laptop
Redis creator antirez built DS4 "Dwarf Star," a pure-C inference engine, using asymmetric quantization to compress DeepSeek V4 Flash from 500GB to 80.8GB for local 128GB unified-memory deployment at 26.7 tokens/sec.
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·6 min
How the Creator of Redis Squeezed a 284-Billion-Parameter DeepSeek Into an Ordinary Laptop
Redis author antirez built the pure-C inference engine DS4 "Dwarf Star," compressing DeepSeek V4 Flash from 500GB to 80.8GB via asymmetric quantization for local deployment on 128GB unified memory at 26.7 tokens/sec.
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·3 min
Jetson Edge AI Development: Setting Up a VS Code + Claude Code Workstation
Set up an AI coding workstation on NVIDIA Jetson using VS Code + Claude Code. Covers JetPack NVIDIA Skills, token budget management, headless SSH dev, and coding agent best practices.
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·4 min
AMD Ryzen AI Halo Real-World Test: Can a Non-Programmer Use Local AI to Write Code?
A non-programmer tests AMD Ryzen AI Halo by deploying local AI models to tackle a real dev task. After testing Ollama and Qwen3, the verdict: AI amplifies developers, it doesn't replace them.
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·4 min
The Local AI Inflection Point: Edge Deployment, Multi-Model Collaboration, and the Open-Source Ecosystem
AI Engineer Summit deep dive: Local AI hits a real inflection point, driven by privacy and cost. Multi-model collaboration goes mainstream, NVIDIA + ExoLabs achieve 10x gains, open-source ecosystem accelerates.
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High-Bandwidth Flash (HBF): A New Path…
·2 min
High-Bandwidth Flash (HBF): A New Path to Breaking the AI Storage Bottleneck
High-Bandwidth Flash (HBF) bridges the gap between HBM and NAND, offering high-bandwidth weight storage at lower cost to tackle the memory wall bottleneck in large AI model inference.
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Using LLMs to Master MikroTik Network …
·2 min
Using LLMs to Master MikroTik Network Configuration: A Practical Guide to AI-Assisted Network Operations
Explore how LLMs can streamline MikroTik RouterOS configuration — from natural language command generation to AI-assisted troubleshooting and security auditing.
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Apple M7 Ultra Leaked: Can 1.5TB Unifi…
·2 min
Apple M7 Ultra Leaked: Can 1.5TB Unified Memory Challenge NVIDIA Blackwell?
Apple's M7 Ultra chip rumored to feature 1.5TB unified memory targeting NVIDIA Blackwell-level AI performance. A deep dive into UMA advantages, what "matching Blackwell" really means, and Apple's AI strategy.
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