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llmfit: One Command to Check Which Loc…

Jul 22, 2026·2 min

llmfit: One Command to Check Which Local LLMs Your Hardware Can Run

llmfit is an open-source Rust CLI tool that predicts whether your local hardware can run a given LLM — no model download required. Covers hundreds of models and backends like Ollama and llama.cpp.

Jul 22, 2026·3 min

Kimi K3 Hands-On: How a 2.8-Trillion-Parameter Open-Source Model Beat Fable5

A US engineer's live test of Kimi K3: 2.8T parameters, 1M token context, 87% audience vote over Fable5 in game generation. Full report covering benchmarks, speed, and code debugging.

Jul 22, 2026·3 min

V100 GPU Showdown: 4×16G PCIe vs. 2×32G SXM — Which Gives You More Bang for Your Buck?

Benchmarking 4×V100 16G PCIe vs. 2×V100 32G SXM adapter for local LLM inference. Prefill speed, decode speed, power limits, and bandwidth bottlenecks analyzed.

Jul 21, 2026·2 min

Qwen3 Fine-Tuning in Practice: A Complete Guide to Local Deployment and Domain Training

A hands-on guide to LLM fine-tuning: from understanding model weights to local Qwen3 deployment, dataset preparation, and domain-specific training. Build a complete AI engineering skill set.

Jul 19, 2026·4 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.

Jul 19, 2026·4 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.

Jul 18, 2026·3 min

AI Coding Agents Explosion: CodeWell Goes Open Source, Kimi K3 Launches, Claude Gets Browser Access

CodeWell open-sources a multi-model terminal coding agent, Kimi K3 launches with ultra-long context, MiniMax Code 2.0 rebuilds its Agent architecture, and Claude gets browser access. AI is accelerating from content generation to task execution.

Jul 17, 2026·2 min

vLLM Inference Framework Deep Dive: A Practical Guide to High-Concurrency DeepSeek Deployment

A deep dive into vLLM's five core features — KV cache management, continuous batching, and distributed inference — plus a full setup guide for deploying DeepSeek on a cloud server.

Jul 17, 2026·2 min

AI Task Routing for Cost Reduction: A Framework for Smaller Teams to Evaluate ROI

Task routing is hailed as a silver bullet for LLM cost reduction, but routing strategy design, model training, and self-hosting each carry hidden engineering costs. This deep dive helps smaller teams evaluate ROI and offers a phased implementation path.

Jul 15, 2026·3 min

The Complete LLM Learning Roadmap: From Beginner to Expert — Courses and Resources Recommended

Confused by scattered LLM resources and unclear learning paths? This guide maps a complete roadmap from basics to advanced, covering Karpathy, Stanford CS224N, DeepLearning.AI, Hugging Face, plus RAG, fine-tuning, and Agent deep dives.

MemStitch Zero-Copy Context Bridging: …

Jul 15, 2026·2 min

MemStitch Zero-Copy Context Bridging: How It Achieves 25x TTFT Speedup in vLLM

A deep dive into how MemStitch's zero-copy context bridging achieves 25x TTFT speedup in vLLM. Covers KV Cache optimization, prefill acceleration, and practical developer value.

Jul 14, 2026·2 min

QuantaMind: An Open-Source Tool for Testing AI Agent Reliability Locally

QuantaMind is a free, open-source local AI Agent reliability testing tool using pass^k scoring and deterministic evaluation, supporting Ollama, llama.cpp, vLLM, and more.

Jul 14, 2026·2 min

Production LLM Deployment Guide: Model Selection, GPU Configuration, and Inference Engine Breakdown

A comprehensive decision framework for production LLM deployment: model selection (open-source vs. API), GPU VRAM configuration, and inference engine comparison including vLLM and TensorRT-LLM.

Jul 13, 2026·2 min

Distributed AI Systems: A Practical Engineering Guide to Training, Inference, and Production Deployment

A deep dive into distributed AI systems engineering: data/model/tensor parallelism for training, KV cache, quantization, elastic scaling for inference, and cloud deployment with Kubernetes, Ray, and DeepSpeed.

Jul 13, 2026·3 min

Distributed AI Systems in Practice: A Complete Guide to Training, Inference, and Production Deployment

A deep dive into Distributed AI Systems: a new book distilling 10 years of AI engineering experience covering distributed training, inference optimization, and production model serving.

Relm: An Open-Source Tool for Integrat…

Jul 13, 2026·3 min

Relm: An Open-Source Tool for Integrating Local LLMs as Native R Objects

Relm wraps local LLMs as native R objects, enabling local inference, data privacy, and interpretability analysis. A deep dive for R-based data scientists.

Jul 13, 2026·3 min

The Rise of Diffusion Language Models: DiffusionGemma Crushes Autoregressive Models in Speed Tests

Diffusion language model DiffusionGemma dramatically outpaces autoregressive Deepseek Flash in speed tests. Explore the tech behind diffusion vs. autoregressive models and their challenges.

Jul 13, 2026·4 min

From Enter to First Token: Decrypting the Full LLM Inference Pipeline (Autoregression, KV Cache & Decoding Strategies)

From pressing Enter to the first character appearing, what happens inside an LLM? This article breaks down autoregressive generation, KV cache acceleration, and decoding strategies like temperature, Top-k, and Top-p.

Jul 13, 2026·4 min

Getting Started with LangChain: LLM Limitations, Agent Principles, and Environment Setup in Practice

An in-depth look at LangChain's core value: the three limitations of LLMs, unified model interfaces, modular architecture, configuring the DeepSeek API, and understanding the SystemMessage/HumanMessage/AIMessage/ToolMessage system to build a foundation for Agent development.

Jul 12, 2026·7 min

Breaking Down the Core Skills of an AI Application Engineer: From Beginner to Industrial-Grade Deployment

Knowing how to call an API doesn't make you an AI engineer. This article breaks down the complete skill structure of an AI application engineer, covering Python fundamentals, LLM fine-tuning, Agent development, and enterprise projects.