<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"><channel><title>Nadhebe — Global AI Engineering Feed</title><description>Independent technical publication and developer toolkit featuring in-depth guides on AI engineering, open-source models, developer workflows, and client-side browser tools.</description><link>https://nadhebe.com/</link><language>en-us</language><ttl>60</ttl><item><title>Bilibili Translator: Real-Time Universal In-Place Translation in All Languages | Nadhebe</title><link>https://nadhebe.com/guides/bilibili-chrome-in-place-translator-guide/</link><guid isPermaLink="true">https://nadhebe.com/guides/bilibili-chrome-in-place-translator-guide/</guid><description>Translate Bilibili into any language in real time across all browsers. Features in-place DOM replacement, 0ms local dictionaries, and Danmaku isolation.</description><pubDate>Mon, 31 Aug 2026 00:00:00 GMT</pubDate><category>Bilibili Translator</category><category>Browser Extension</category><category>Multi-Language Translation</category><category>Vue 3 Hydration</category><category>DOM Manipulation</category><category>Web Development</category><category>Danmaku Isolation</category><category>Manifest V3</category><author>nadhebe-team</author><enclosure url="https://nadhebe.com/images/bilibili-in-place-translator-chrome-extension-hero.webp" length="0" type="image/jpeg"/></item><item><title>Fine-Tuning DeepSeek-R1 Distill with Unsloth on Consumer GPUs: Complete Walkthrough</title><link>https://nadhebe.com/tutorials/fine-tune-deepseek-r1-unsloth-gpu/</link><guid isPermaLink="true">https://nadhebe.com/tutorials/fine-tune-deepseek-r1-unsloth-gpu/</guid><description>Step-by-step guide to fine-tuning DeepSeek-R1 Distill reasoning models on a single 16GB or 24GB GPU using Unsloth 2x faster kernels, QLoRA, and GGUF export.</description><pubDate>Sat, 29 Aug 2026 00:00:00 GMT</pubDate><category>deepseek-r1</category><category>unsloth</category><category>fine-tuning</category><category>qlora</category><category>gpu</category><category>ollama</category><category>tutorials</category><author>nadhebe-team</author><enclosure url="https://nadhebe.com/images/fine-tune-deepseek-r1-unsloth-gpu-hero.webp" length="0" type="image/jpeg"/></item><item><title>Kokoro TTS vs ElevenLabs: Self-Hosting Ultra-Realistic 82M Voice AI for $0</title><link>https://nadhebe.com/comparisons/kokoro-tts-vs-elevenlabs/</link><guid isPermaLink="true">https://nadhebe.com/comparisons/kokoro-tts-vs-elevenlabs/</guid><description>Compare Kokoro TTS 82M open-source speech model with ElevenLabs. Benchmark latency, audio quality, self-hosting Docker setup, and cloud API cost savings.</description><pubDate>Sat, 29 Aug 2026 00:00:00 GMT</pubDate><category>kokoro-tts</category><category>elevenlabs</category><category>text-to-speech</category><category>voice-ai</category><category>self-hosting</category><category>docker</category><category>comparisons</category><author>nadhebe-team</author><enclosure url="https://nadhebe.com/images/kokoro-tts-vs-elevenlabs-hero.webp" length="0" type="image/jpeg"/></item><item><title>Mem0 vs GraphRAG vs Vector RAG: Building Production Long-Term Memory for AI Agents</title><link>https://nadhebe.com/comparisons/mem0-vs-graphrag-vs-vector-rag/</link><guid isPermaLink="true">https://nadhebe.com/comparisons/mem0-vs-graphrag-vs-vector-rag/</guid><description>Compare Mem0, Microsoft GraphRAG, and traditional Vector RAG for AI agent memory. Benchmark multi-hop reasoning, latency, update costs, and state persistence.</description><pubDate>Sat, 29 Aug 2026 00:00:00 GMT</pubDate><category>mem0</category><category>graphrag</category><category>vector-rag</category><category>agentic-ai</category><category>rag</category><category>long-term-memory</category><category>comparisons</category><author>nadhebe-team</author><enclosure url="https://nadhebe.com/images/mem0-vs-graphrag-vs-vector-rag-hero.webp" length="0" type="image/jpeg"/></item><item><title>Claude 3.7 Sonnet Hybrid Reasoning: When to Use Thinking Tokens vs Standard Fast Mode</title><link>https://nadhebe.com/guides/claude-3-7-sonnet-hybrid-reasoning-guide/</link><guid isPermaLink="true">https://nadhebe.com/guides/claude-3-7-sonnet-hybrid-reasoning-guide/</guid><description>Master Claude 3.7 Sonnet&apos;s hybrid reasoning architecture. Learn how to configure dynamic thinking budgets, benchmark against o3-mini, and optimize API costs.</description><pubDate>Sat, 29 Aug 2026 00:00:00 GMT</pubDate><category>claude-3-7</category><category>anthropic</category><category>hybrid-reasoning</category><category>extended-thinking</category><category>llm-benchmarks</category><category>prompt-engineering</category><author>nadhebe-team</author><enclosure url="https://nadhebe.com/images/claude-3-7-sonnet-hybrid-reasoning-hero.webp" length="0" type="image/jpeg"/></item><item><title>Speculative Decoding in vLLM &amp; SGLang: 3x LLM Inference Speedup Guide</title><link>https://nadhebe.com/guides/speculative-decoding-vllm-sglang-guide/</link><guid isPermaLink="true">https://nadhebe.com/guides/speculative-decoding-vllm-sglang-guide/</guid><description>Accelerate LLM inference throughput and reduce latency by up to 3x using speculative decoding, draft models, and Medusa heads in vLLM and SGLang.</description><pubDate>Sat, 29 Aug 2026 00:00:00 GMT</pubDate><category>speculative-decoding</category><category>vllm</category><category>sglang</category><category>llm-inference</category><category>performance</category><category>gpu-optimization</category><category>guides</category><author>nadhebe-team</author><enclosure url="https://nadhebe.com/images/speculative-decoding-vllm-sglang-hero.webp" length="0" type="image/jpeg"/></item><item><title>How to Create AI Influencer Video Ads with ChatGPT &amp; Google Flow: 3-Scene Visual Continuity Guide</title><link>https://nadhebe.com/tutorials/ai-character-video-ads-google-flow-chatgpt/</link><guid isPermaLink="true">https://nadhebe.com/tutorials/ai-character-video-ads-google-flow-chatgpt/</guid><description>Master step-by-step workflow for generating photorealistic AI characters in ChatGPT and directing 30-second multi-scene video ads in Google Flow with zero drift.</description><pubDate>Sun, 09 Aug 2026 00:00:00 GMT</pubDate><category>google-flow</category><category>ai-video</category><category>chatgpt</category><category>prompts</category><category>video-ads</category><category>tutorials</category><author>nadhebe-team</author><enclosure url="https://nadhebe.com/images/ai-character-video-ads-google-flow-hero.png" length="0" type="image/jpeg"/></item><item><title>How to Create AI Influencer Presenters with ChatGPT &amp; Google Flow Omni: Long-Form YouTube Guide</title><link>https://nadhebe.com/tutorials/google-flow-omni-ai-influencer-presenter-guide/</link><guid isPermaLink="true">https://nadhebe.com/tutorials/google-flow-omni-ai-influencer-presenter-guide/</guid><description>Step-by-step tutorial on rendering photorealistic AI character portraits with ChatGPT and generating continuous long-form YouTube presenter videos in Google Flow Omni.</description><pubDate>Sun, 09 Aug 2026 00:00:00 GMT</pubDate><category>google-flow</category><category>ai-video</category><category>chatgpt</category><category>prompts</category><category>youtube-automation</category><category>tutorials</category><author>nadhebe-team</author><enclosure url="https://nadhebe.com/images/google-flow-omni-influencer-hero.webp" length="0" type="image/jpeg"/></item><item><title>NotebookLM Audio Overviews &amp; Source Grounding Developer Tutorial</title><link>https://nadhebe.com/tutorials/notebooklm-audio-overviews-source-grounding-tutorial/</link><guid isPermaLink="true">https://nadhebe.com/tutorials/notebooklm-audio-overviews-source-grounding-tutorial/</guid><description>Learn how to build, customize, and steer Google NotebookLM Audio Overviews, synthesize multi-document knowledge graphs, and enforce strict source attribution.</description><pubDate>Sat, 08 Aug 2026 00:00:00 GMT</pubDate><category>notebooklm</category><category>google-ai</category><category>rag</category><category>audio-overviews</category><category>source-grounding</category><category>knowledge-synthesis</category><author>nadhebe-team</author><enclosure url="https://nadhebe.com/images/notebooklm-audio-overviews-hero.png" length="0" type="image/jpeg"/></item><item><title>Google AI Studio System Prompts &amp; Structured Outputs Architecture Guide</title><link>https://nadhebe.com/guides/google-ai-studio-system-prompts-structured-output-guide/</link><guid isPermaLink="true">https://nadhebe.com/guides/google-ai-studio-system-prompts-structured-output-guide/</guid><description>A comprehensive guide on configuring system instructions, JSON Schema structured outputs, function calling, and temperature parameters in Google AI Studio for production AI applications.</description><pubDate>Sat, 08 Aug 2026 00:00:00 GMT</pubDate><category>google-ai-studio</category><category>gemini-api</category><category>structured-outputs</category><category>system-prompts</category><category>pydantic</category><category>json-schema</category><author>nadhebe-team</author><enclosure url="https://nadhebe.com/images/google-ai-studio-system-prompts-hero.png" length="0" type="image/jpeg"/></item><item><title>Generative Engine Optimization (GEO): Technical Architecture and Ranking Protocols</title><link>https://nadhebe.com/guides/generative-engine-optimization-geo-guide/</link><guid isPermaLink="true">https://nadhebe.com/guides/generative-engine-optimization-geo-guide/</guid><description>Definitive technical guide to Generative Engine Optimization (GEO). Learn RAG grounding mechanics, query fan-out deconstruction, JSON-LD schema engineering, and AI overview audit protocols.</description><pubDate>Thu, 06 Aug 2026 12:00:00 GMT</pubDate><category>Generative Engine Optimization</category><category>GEO</category><category>SEO Strategy</category><category>RAG Grounding</category><category>JSON-LD Schema</category><category>AI Overviews</category><category>Search Architecture</category><author>nadhebe-team</author><enclosure url="https://nadhebe.com/images/generative-engine-optimization-geo-guide-hero.png" length="0" type="image/jpeg"/></item><item><title>Self-Hosting LLMs vs API Costs: Break-Even Math Guide</title><link>https://nadhebe.com/guides/self-hosting-llms-vs-api-cost-breakdown/</link><guid isPermaLink="true">https://nadhebe.com/guides/self-hosting-llms-vs-api-cost-breakdown/</guid><description>Comprehensive financial math guide for self-hosting LLMs versus using cloud APIs. Includes GPU TCO formulas, break-even token volume curves, and server energy cost analysis.</description><pubDate>Thu, 06 Aug 2026 11:00:00 GMT</pubDate><category>LLM Self-Hosting</category><category>Cloud API Costs</category><category>GPU Infrastructure</category><category>vLLM</category><category>Cost Optimization</category><category>FinOps</category><category>Enterprise AI</category><author>nadhebe-team</author><enclosure url="https://nadhebe.com/images/self-hosting-llms-vs-api-cost-breakdown-hero.png" length="0" type="image/jpeg"/></item><item><title>How to Build Local Agentic RAG Workflows using LangGraph and Ollama</title><link>https://nadhebe.com/tutorials/agentic-rag-workflows-langgraph/</link><guid isPermaLink="true">https://nadhebe.com/tutorials/agentic-rag-workflows-langgraph/</guid><description>Step-by-step developer tutorial to build stateful agentic RAG workflows using LangGraph, Ollama, and ChromaDB locally without cloud API keys.</description><pubDate>Thu, 06 Aug 2026 00:00:00 GMT</pubDate><category>LangGraph</category><category>Agentic RAG</category><category>Ollama</category><category>ChromaDB</category><category>Python</category><category>Local AI</category><category>AI Agents</category><author>nadhebe-team</author><enclosure url="https://nadhebe.com/images/agentic-rag-workflows-langgraph-hero.png" length="0" type="image/jpeg"/></item><item><title>Deploying DeepSeek-OCR on Local GPUs for High-Volume Data Pipelines</title><link>https://nadhebe.com/tutorials/deepseek-ocr-local-gpu-deployment/</link><guid isPermaLink="true">https://nadhebe.com/tutorials/deepseek-ocr-local-gpu-deployment/</guid><description>Step-by-step tutorial to deploy DeepSeek-OCR locally on GPUs for document extraction. Includes context compression math, PyTorch pipelines, layout parsing, and Docker configs.</description><pubDate>Thu, 06 Aug 2026 00:00:00 GMT</pubDate><category>DeepSeek-OCR</category><category>Vision AI</category><category>PyTorch</category><category>Local GPU</category><category>Document Processing</category><category>Docker</category><category>Data Pipelines</category><author>nadhebe-team</author><enclosure url="https://nadhebe.com/images/deepseek-ocr-local-gpu-deployment-hero.png" length="0" type="image/jpeg"/></item><item><title>Model Context Protocol (MCP) Architecture and Production API Tutorial</title><link>https://nadhebe.com/tutorials/model-context-protocol-mcp-guide/</link><guid isPermaLink="true">https://nadhebe.com/tutorials/model-context-protocol-mcp-guide/</guid><description>Comprehensive developer tutorial on Model Context Protocol (MCP) architecture. Learn JSON-RPC schema transport over stdio/SSE, tool definition syntax, and Python implementation.</description><pubDate>Thu, 06 Aug 2026 00:00:00 GMT</pubDate><category>Model Context Protocol</category><category>MCP</category><category>AI Infrastructure</category><category>Claude Code</category><category>Python</category><category>JSON-RPC</category><category>API Architecture</category><author>nadhebe-team</author><enclosure url="https://nadhebe.com/images/model-context-protocol-mcp-guide-hero.webp" length="0" type="image/jpeg"/></item><item><title>Running Qwen 3.5 27B on Consumer GPUs: VRAM Setup Guide</title><link>https://nadhebe.com/tutorials/qwen-3-5-27b-consumer-gpu-setup/</link><guid isPermaLink="true">https://nadhebe.com/tutorials/qwen-3-5-27b-consumer-gpu-setup/</guid><description>Hardware setup tutorial to run Qwen 3.5 27B locally on consumer GPUs. Includes INT4 GGUF quantization, FlashAttention-2 compilation, and multi-GPU tensor parallelism.</description><pubDate>Thu, 06 Aug 2026 00:00:00 GMT</pubDate><category>Qwen 3.5</category><category>Local LLM</category><category>Consumer GPU</category><category>FlashAttention-2</category><category>Ollama</category><category>VRAM Optimization</category><category>vLLM</category><author>nadhebe-team</author><enclosure url="https://nadhebe.com/images/qwen-3-5-27b-consumer-gpu-setup-hero.webp" length="0" type="image/jpeg"/></item><item><title>Running Flux.1 Local Image Generation on Consumer GPUs</title><link>https://nadhebe.com/tutorials/run-flux-1-locally-consumer-gpu/</link><guid isPermaLink="true">https://nadhebe.com/tutorials/run-flux-1-locally-consumer-gpu/</guid><description>Developer tutorial to run Flux.1 open diffusion models locally on consumer GPUs using ComfyUI. Covers Schnell vs Dev, NF4 quantization, 8GB VRAM offloading, and LoRA setup.</description><pubDate>Thu, 06 Aug 2026 00:00:00 GMT</pubDate><category>Flux.1</category><category>ComfyUI</category><category>Local AI</category><category>Consumer GPU</category><category>Image Generation</category><category>NF4 Quantization</category><category>Diffusion Models</category><author>nadhebe-team</author><enclosure url="https://nadhebe.com/images/run-flux-1-locally-consumer-gpu-hero.webp" length="0" type="image/jpeg"/></item><item><title>How to Run DeepSeek R1 Locally with Ollama: Complete Guide</title><link>https://nadhebe.com/tutorials/run-deepseek-r1-locally-ollama/</link><guid isPermaLink="true">https://nadhebe.com/tutorials/run-deepseek-r1-locally-ollama/</guid><description>Complete developer setup guide to run DeepSeek R1 locally using Ollama. Includes VRAM memory formulas, GGUF quantization comparisons, CLI integration, and ChromaDB Python code.</description><pubDate>Thu, 06 Aug 2026 00:00:00 GMT</pubDate><category>DeepSeek R1</category><category>Ollama</category><category>Local LLM</category><category>AI Engineering</category><category>VRAM Optimization</category><category>ChromaDB</category><author>nadhebe-team</author><enclosure url="https://nadhebe.com/images/run-deepseek-r1-locally-ollama-hero.png" length="0" type="image/jpeg"/></item><item><title>Optimizing KV Cache Utilization in vLLM Production Clusters</title><link>https://nadhebe.com/tutorials/vllm-kv-cache-optimization-guide/</link><guid isPermaLink="true">https://nadhebe.com/tutorials/vllm-kv-cache-optimization-guide/</guid><description>Production tutorial to optimize KV cache utilization in vLLM. Covers PagedAttention virtual memory mapping, memory fragmentation fixes, and prefix caching CLI configs.</description><pubDate>Thu, 06 Aug 2026 00:00:00 GMT</pubDate><category>vLLM</category><category>KV Cache</category><category>PagedAttention</category><category>GPU Optimization</category><category>Python</category><category>Kubernetes</category><category>AI Infrastructure</category><author>nadhebe-team</author><enclosure url="https://nadhebe.com/images/vllm-kv-cache-optimization-guide-hero.webp" length="0" type="image/jpeg"/></item><item><title>DeepSeek V4 vs OpenAI o3-mini vs Claude 3.7 Sonnet Benchmark</title><link>https://nadhebe.com/comparisons/deepseek-v4-vs-o3-mini-vs-claude/</link><guid isPermaLink="true">https://nadhebe.com/comparisons/deepseek-v4-vs-o3-mini-vs-claude/</guid><description>Head-to-head benchmark comparison of frontier AI reasoning models: DeepSeek V4, OpenAI o3-mini, and Claude 3.7 Sonnet. Evaluates coding pass rates, math accuracy, and API pricing.</description><pubDate>Thu, 06 Aug 2026 00:00:00 GMT</pubDate><category>DeepSeek V4</category><category>OpenAI o3-mini</category><category>Claude 3.7 Sonnet</category><category>AI Benchmarks</category><category>Reasoning Models</category><category>Code Generation</category><category>Model Comparison</category><author>nadhebe-team</author><enclosure url="https://nadhebe.com/images/deepseek-v4-vs-o3-mini-vs-claude-hero.png" length="0" type="image/jpeg"/></item><item><title>NVIDIA Blackwell B200 vs Hopper H200 LLM Inference Analysis</title><link>https://nadhebe.com/comparisons/nvidia-b200-vs-h200-llm-inference/</link><guid isPermaLink="true">https://nadhebe.com/comparisons/nvidia-b200-vs-h200-llm-inference/</guid><description>Architectural benchmark comparison of NVIDIA Blackwell B200 vs Hopper H200 for LLM inference. Evaluates HBM3e memory bandwidth, FP4 FLOPS throughput, and TCO.</description><pubDate>Thu, 06 Aug 2026 00:00:00 GMT</pubDate><category>NVIDIA B200</category><category>NVIDIA H200</category><category>Blackwell</category><category>Hopper</category><category>GPU Benchmarks</category><category>LLM Inference</category><category>HBM3e</category><category>AI Hardware</category><author>nadhebe-team</author><enclosure url="https://nadhebe.com/images/nvidia-b200-vs-h200-llm-inference-hero.webp" length="0" type="image/jpeg"/></item><item><title>Best Local LLMs for 8GB VRAM Consumer GPUs: Hardware Benchmarks</title><link>https://nadhebe.com/guides/best-local-llms-8gb-vram/</link><guid isPermaLink="true">https://nadhebe.com/guides/best-local-llms-8gb-vram/</guid><description>Hardware benchmark guide evaluating the best open-weight local LLMs for 8GB VRAM consumer GPUs. Includes token-per-second decoding speeds, context spillover, and quantization metrics.</description><pubDate>Thu, 06 Aug 2026 00:00:00 GMT</pubDate><category>8GB VRAM</category><category>Local LLM</category><category>Ollama</category><category>GPU Benchmarks</category><category>Qwen 2.5</category><category>Llama 3.1</category><category>Phi-4 Mini</category><category>AI Hardware</category><author>nadhebe-team</author><enclosure url="https://nadhebe.com/images/best-local-llms-8gb-vram-hero.png" length="0" type="image/jpeg"/></item><item><title>FP4 vs FP8 vs INT4 Quantization: Performance &amp; Accuracy</title><link>https://nadhebe.com/guides/fp4-vs-fp8-vs-int4-quantization/</link><guid isPermaLink="true">https://nadhebe.com/guides/fp4-vs-fp8-vs-int4-quantization/</guid><description>Technical comparison guide analyzing FP4, FP8, and INT4 quantization formats. Evaluates micro-scaling formats, hardware acceleration across NVIDIA Hopper &amp; Blackwell, and accuracy.</description><pubDate>Thu, 06 Aug 2026 00:00:00 GMT</pubDate><category>FP4</category><category>FP8</category><category>INT4</category><category>Quantization</category><category>NVIDIA Blackwell</category><category>TensorRT-LLM</category><category>vLLM</category><category>GPU Architecture</category><author>nadhebe-team</author><enclosure url="https://nadhebe.com/images/fp4-vs-fp8-vs-int4-quantization-hero.webp" length="0" type="image/jpeg"/></item><item><title>Google NotebookLM Pro 2026 Developer Workflows and Integration Protocols</title><link>https://nadhebe.com/guides/notebooklm-pro-developer-workflows/</link><guid isPermaLink="true">https://nadhebe.com/guides/notebooklm-pro-developer-workflows/</guid><description>Developer workflows guide for Google NotebookLM Pro. Learn source document ingestion limits, multi-file context indexing, Audio Overview podcast pipelines, and API integrations.</description><pubDate>Thu, 06 Aug 2026 00:00:00 GMT</pubDate><category>NotebookLM Pro</category><category>Google AI</category><category>Knowledge Management</category><category>Audio Overview</category><category>Developer Workflows</category><category>AI Research</category><category>Gemini 2.0</category><author>nadhebe-team</author><enclosure url="https://nadhebe.com/images/notebooklm-pro-developer-workflows-hero.png" length="0" type="image/jpeg"/></item><item><title>Complete Guide to Ollama Model Quantization Formats (Q4_K_M vs Q8_0 vs EXL2)</title><link>https://nadhebe.com/guides/ollama-quantization-formats-compared/</link><guid isPermaLink="true">https://nadhebe.com/guides/ollama-quantization-formats-compared/</guid><description>Technical comparison guide evaluating Ollama GGUF quantization formats. Compares Q4_K_M, Q5_K_M, Q8_0, and EXL2 across perplexity, VRAM savings, and decode speed.</description><pubDate>Thu, 06 Aug 2026 00:00:00 GMT</pubDate><category>Ollama</category><category>Quantization</category><category>GGUF</category><category>Q4_K_M</category><category>Q8_0</category><category>EXL2</category><category>VRAM Optimization</category><category>Local LLM</category><author>nadhebe-team</author><enclosure url="https://nadhebe.com/images/ollama-quantization-formats-compared-hero.webp" length="0" type="image/jpeg"/></item><item><title>Top 8 Best AI Coding Tools for Developers in 2026: Benchmark and Feature Comparison</title><link>https://nadhebe.com/reviews/best-ai-coding-tools-2026/</link><guid isPermaLink="true">https://nadhebe.com/reviews/best-ai-coding-tools-2026/</guid><description>A comprehensive roundup review comparing the best AI coding tools in 2026—Claude Code, Cursor, Windsurf, GitHub Copilot, Supermaven, Cody, and Aider.</description><pubDate>Tue, 04 Aug 2026 00:00:00 GMT</pubDate><category>AI Coding</category><category>Claude Code</category><category>Cursor</category><category>Windsurf</category><category>GitHub Copilot</category><category>Supermaven</category><category>Aider</category><category>Developer Tools</category><author>nadhebe-team</author><enclosure url="https://nadhebe.com/images/best-ai-coding-tools-hero.webp" length="0" type="image/jpeg"/></item><item><title>Top 7 Best Cloud GPU Providers for AI Training and vLLM Inference in 2026</title><link>https://nadhebe.com/reviews/best-cloud-gpu-providers-2026/</link><guid isPermaLink="true">https://nadhebe.com/reviews/best-cloud-gpu-providers-2026/</guid><description>An in-depth comparative evaluation of the best cloud GPU providers—RunPod, Modal, Lambda Labs, Vast.ai, Together AI, Replicate, and CoreWeave.</description><pubDate>Tue, 04 Aug 2026 00:00:00 GMT</pubDate><category>GPU Cloud</category><category>RunPod</category><category>Modal</category><category>Lambda Labs</category><category>Vast.ai</category><category>vLLM</category><category>H100</category><category>Cloud Compute</category><author>nadhebe-team</author><enclosure url="https://nadhebe.com/images/best-cloud-gpu-providers-hero.webp" length="0" type="image/jpeg"/></item><item><title>Top 10 Model Context Protocol (MCP) Servers for AI Developers in 2026</title><link>https://nadhebe.com/reviews/best-mcp-servers-2026/</link><guid isPermaLink="true">https://nadhebe.com/reviews/best-mcp-servers-2026/</guid><description>A comprehensive roundup review of the best Model Context Protocol (MCP) servers for database management, web search, GitHub workflows, and cloud edge tools.</description><pubDate>Tue, 04 Aug 2026 00:00:00 GMT</pubDate><category>MCP</category><category>Model Context Protocol</category><category>AI Tools</category><category>Developer Tools</category><category>PostgreSQL</category><category>GitHub</category><category>Cloudflare</category><author>nadhebe-team</author><enclosure url="https://nadhebe.com/images/best-mcp-servers-hero.webp" length="0" type="image/jpeg"/></item><item><title>Cloudflare Workers AI Code Mode: Building Edge Agents with Stateless MCP Handlers</title><link>https://nadhebe.com/tutorials/cloudflare-workers-ai-code-mode-mcp/</link><guid isPermaLink="true">https://nadhebe.com/tutorials/cloudflare-workers-ai-code-mode-mcp/</guid><description>Discover Cloudflare Workers AI Code Mode, replacing verbose JSON tool calling with programmatic executable code blocks for stateless MCP handlers.</description><pubDate>Mon, 03 Aug 2026 00:00:00 GMT</pubDate><category>Cloudflare Workers</category><category>Code Mode</category><category>MCP</category><category>Edge AI</category><category>Agents SDK</category><category>TypeScript</category><author>nadhebe-team</author><enclosure url="https://nadhebe.com/images/cloudflare-workers-ai-code-mode-hero.webp" length="0" type="image/jpeg"/></item><item><title>Claude Code Troubleshooting Guide: Fixing OAuth Errors, 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type="image/jpeg"/></item><item><title>vLLM CUDA Out of Memory (OOM): Fixes for max_model_len, gpu_memory_utilization, and PagedAttention</title><link>https://nadhebe.com/tutorials/vllm-cuda-out-of-memory-fix/</link><guid isPermaLink="true">https://nadhebe.com/tutorials/vllm-cuda-out-of-memory-fix/</guid><description>Resolve vLLM CUDA Out of Memory errors when serving DeepSeek R1 and Llama models using VRAM allocation flags, KV cache quantization, and tensor parallelism.</description><pubDate>Mon, 03 Aug 2026 00:00:00 GMT</pubDate><category>vLLM</category><category>CUDA OOM</category><category>Troubleshooting</category><category>GPU VRAM</category><category>DeepSeek R1</category><category>PagedAttention</category><author>nadhebe-team</author><enclosure url="https://nadhebe.com/images/vllm-cuda-out-of-memory-hero.webp" length="0" type="image/jpeg"/></item><item><title>Claude CLI vs Gemini CLI: Terminal AI Tools &amp; Developer Agent 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