Ollama
Best Ways to Connect Local AI to Notion in 2026
4 real ways to connect Notion to a local LLM without sending data to the cloud. MCP servers, RAG pipelines, Open WebUI, and n8n workflows compared with setup steps.
RAG Pipeline for Local AI: A Practical Guide to Retrieval-Augmented Generation
Build a local RAG pipeline with Ollama, ChromaDB, and your own documents. Chunking strategies, embedding models, vector stores, and the failure modes nobody warns you about.
Local AI for Accounting and Tax: Keep Your Financial Data Off the Cloud
Local LLMs can categorize transactions, draft client letters, extract receipt data, and answer questions over tax documents — without sending a single number to OpenAI or Google. What works, what doesn't, and how to set it up.
Home Assistant + Local LLM: Voice Control Your Smart Home Without the Cloud
Set up fully local voice control with Home Assistant, Ollama, Whisper, and Piper. No Alexa, no cloud, no subscriptions. Wyoming protocol pipeline, model picks, and hardware options.
Running OpenClaw on 4GB, 6GB, and 8GB GPUs: What Actually Works
OpenClaw on low VRAM GPUs: 4GB is rough, 6GB is marginal, 8GB is where it starts working. Model picks, quantization tricks, partial offload, and when to just use a cloud API instead.
OpenClaw on Raspberry Pi: What Actually Works (and What Doesn't)
Pi 5 with 8GB RAM runs OpenClaw as a gateway with cloud APIs. Local LLMs hit 2-7 tok/s on 1.5B-3B models. Step-by-step setup for llama.cpp, Ollama, and OpenClaw on ARM64.
LLM Running Slow? Two Different Problems, Two Different Fixes
Slow local LLM? Separate time-to-first-token from generation speed. Fix prompt processing with batch size and Flash Attention. Fix tok/s with GPU layers, quantization, and context length.
Local AI for Therapists: Session Notes, Treatment Plans, and Client Privacy Without the Cloud
Run AI on your own hardware to draft session notes, treatment plans, and clinical letters without sending client data to OpenAI. HIPAA-friendly setup for therapists.
Local AI for Small Business: Email, Invoicing, and Customer Support Without Monthly Subscriptions
A 5-person team spends $1,500-3,000/year on AI subscriptions. A $600 mini PC running Ollama replaces all of them. Here's the setup, the workflows, and the math.
Docker for Local AI: The Complete Setup Guide for Ollama, Open WebUI, and GPU Passthrough
Run Ollama and Open WebUI in Docker with GPU passthrough. Five copy-paste compose files for NVIDIA, AMD, multi-GPU, and CPU-only setups, plus the Mac gotcha most guides skip.
Why Your Local LLM Is Slow: The num_ctx VRAM Overflow Nobody Warns You About
DeepSeek-R1 14B went from 35 tok/s to 4.8 tok/s on the same GPU. The fix was one parameter. How num_ctx silently overflows VRAM and kills inference speed.
Qwen 3.5 Small Models: The 9B Beats Last-Gen 30B — Here's What Matters for Local AI
Alibaba's Qwen 3.5 drops 4 small models (0.8B to 9B) — all natively multimodal, 262K context, Apache 2.0. The 9B beats Qwen3-30B on reasoning and destroys GPT-5-Nano on vision. VRAM tables and what to run.
Best 8GB GPU Model: How to Set Up Qwen 3.5 9B (Step by Step)
Qwen 3.5 9B fits in 6.6GB and beats models 3x its size. Complete setup with Ollama, benchmarks, and real-world testing on RTX 3060 and 4060.
WSL2 + Ollama on Windows: Complete Setup Guide (GPU Passthrough Included)
Install Ollama in WSL2 with full GPU acceleration in 20 minutes. GPU passthrough, Open WebUI, Docker Compose, VPN fixes, and the gotchas that will waste your afternoon.
Run Your Coding Agent on Local Models with PI Agent + Ollama
PI Agent is a free, open-source coding agent that works with any model. Set up PI + Ollama to run a private coding agent on Qwen 3.5 or Qwen3-Coder-Next with zero API costs.
Claude Code vs PI Agent — Which Coding Agent for Local AI?
Claude Code vs PI Agent compared for local AI development. System prompts, tools, pricing, local model support, and honest verdicts for every type of developer.
Best Qwen 3.5 Models Ranked: Every Size, Every GPU, Every Quant
Complete ranking of all Qwen 3.5 models from 0.8B to 397B. VRAM requirements, speed benchmarks, and which model to pick for your hardware.
OpenClaw on Mac: Setup, Optimization, and What Actually Works
brew install openclaw-cli, connect Ollama, configure the gateway, and stop fighting macOS. Apple Silicon setup, memory math, launchd config, and the gotchas nobody warns you about.
What Can You Run on 8GB Apple Silicon? Local AI on a Budget Mac
Llama 3.2 3B runs at 30 tok/s. Phi-4 Mini fits with room to spare. 7B models technically load but swap to disk. Honest benchmarks and real limits for 8GB M1/M2/M3/M4 Macs.
Open WebUI Not Connecting to Ollama? Every Fix
Docker networking, wrong OLLAMA_BASE_URL, localhost confusion, WSL2 isolation, missing models, random disconnects. Every Open WebUI + Ollama connection problem with the exact fix.
Ollama on Mac: Setup and Optimization Guide (2026)
Install Ollama on Apple Silicon, verify Metal GPU is active, and tune it for your Mac's RAM. Config for M1 through M4 Ultra with model picks per memory tier.
Ollama on Mac Not Working? Fix Metal, Memory Pressure, and Slow Performance
ollama ps says CPU? Generation crawling at 2 tok/s? macOS killed your model mid-sentence? Every Mac-specific Ollama problem diagnosed and fixed with exact commands.
LM Studio vs Ollama on Mac: Which Should You Use?
LM Studio's MLX backend is 20-30% faster and uses half the memory. Ollama is lighter, always-on, and better for APIs. Mac-specific benchmarks and when to use each.
Best Way to Run Qwen 3.5 on Mac: MLX vs Ollama Speed Test
MLX runs Qwen 3.5 up to 2x faster than Ollama on Apple Silicon. Head-to-head benchmarks on M1 through M4, with setup instructions for both.
Obsidian + Local LLM: Build a Private AI Second Brain
Connect Obsidian to a local LLM via Ollama for private AI-powered note search, summaries, and chat. Step-by-step setup with Copilot and Smart Connections.
Building AI Agents with Local LLMs: A Practical Guide
Build AI agents with local LLMs using Ollama and Python. Model requirements, VRAM budgets, framework comparison, working code example, and security warnings.
Best New Ollama 0.17 Features: ollama launch, MLX, and OpenClaw Support
Everything new in Ollama 0.16 through 0.17.7: ollama launch for coding tools, native MLX on Apple Silicon, OpenClaw integration, web search API, and image generation. Updated March 2026.
SmarterRouter: A VRAM-Aware LLM Gateway for Your Local AI Lab
Intelligent router that profiles your models, manages VRAM, caches responses semantically, and auto-picks the best model per prompt. Works with Ollama and llama.cpp.
Why Is My Local LLM So Slow? A Diagnostic Guide
Local LLM running slow? Check GPU vs CPU inference, VRAM offloading, quantization, context length, backend choice, and thermals. Find your fix in 60 seconds.
Ollama Not Using GPU: Complete Fix Guide
Ollama running on CPU instead of GPU? Diagnose with ollama ps and nvidia-smi, then fix CUDA drivers, ROCm setup, VRAM limits, and Docker GPU passthrough.
Ollama API Connection Refused: Quick Fixes
Ollama API returning connection refused? Check if it's running, fix the port, open it to the network, and solve Docker and WSL2 connectivity issues.
Model Outputs Garbage: Debugging Bad Generations
Local LLM outputs repetitive loops, gibberish, or wrong answers? Seven causes with exact fixes — from corrupted downloads to wrong chat templates.
Memory Leak in Long Conversations: Causes and Fixes
VRAM climbs with every message until your model crashes? It's probably KV cache growth, not a leak. How to diagnose, monitor, and fix memory issues in local LLMs.
GGUF File Won't Load: Format and Compatibility Fixes
GGUF model won't load? Version mismatch, corrupted download, wrong format, split files, or memory issues. Find your error and fix it in under a minute.
CUDA Out of Memory: What It Means and How to Fix It
CUDA out of memory means your model doesn't fit in VRAM. Seven fixes ranked by effort — context length, KV cache quantization, model quant, CPU offload — with tool-specific commands for Ollama, llama.cpp, and LM Studio.
Mac Mini M4 for Local AI: Which Config to Buy and What It Actually Runs
Mac Mini M4 Pro 48GB runs Qwen3-32B at 15-22 tok/s, draws 40W under load, and costs $25/year in electricity. Which config to buy and what each runs.
Qwen3 Complete Guide: Every Model from 0.6B to 235B
Qwen3 is the best open model family for budget local AI. Dense models from 0.6B to 32B, MoE models that punch above their weight, and a /think toggle no one else has.
Llama 4 Guide: Running Scout and Maverick Locally
Complete Llama 4 guide for local AI — Scout (109B MoE, 17B active) and Maverick (400B). VRAM requirements, Ollama setup, benchmarks, and honest hardware reality check.
GPT-OSS Guide: OpenAI's First Open Model for Local AI
GPT-OSS 20B is OpenAI's first open-weight model. MoE with 3.6B active params, MXFP4 at 13GB, 128K context, Apache 2.0. Here's how to run it.
DeepSeek V3.2 Guide: What Changed and How to Run It Locally
DeepSeek V3.2 competes with GPT-5 on benchmarks. The full model needs 350GB+ VRAM. But the R1 distills run on a $200 used GPU — and they're shockingly good.
Running OpenClaw 100% Local — Zero API Costs
Configure OpenClaw to run entirely through Ollama with no API keys, no cloud calls, and no monthly bills. Full setup guide with model picks by VRAM tier.
OpenClaw Model Routing: Cheap Models for Simple Tasks, Smart Models When Needed
Stop paying Opus prices for heartbeats. Set up tiered model routing in openclaw.json so cheap models handle 80% of work and frontier models only fire when needed.
How to Update Models in Ollama — Keep Your Local LLMs Current
Ollama doesn't auto-update models. Run ollama pull model:tag to grab the latest version — only changed layers download. Use ollama show to check what you have, and a simple loop to update everything at once.
From 178 Seconds to 19: How a WiFi Laptop Borrowed a GPU's Brain
A WiFi laptop with no GPU ran inference in 19 seconds by borrowing an RTX 3090 across the network. The same query took 178 seconds on CPU. Here's how mycoSwarm's Tailscale mesh made it work.
Function Calling with Local LLMs: Tools, Agents, and Structured Output
Function calling with local LLMs using Ollama and llama.cpp. Qwen 2.5 7B matches GPT-4 accuracy for tool selection. Working code and agentic loop patterns.
Building a Local AI Assistant: Your Private Jarvis
Build a private AI assistant with Ollama, Open WebUI, Whisper, and Kokoro TTS. Voice chat, document Q&A, home automation — all local, no cloud, no subscriptions.
Structured Output from Local LLMs: JSON, YAML, and Schemas
Ollama's format parameter guarantees valid JSON from any local model. Grammar constraints in llama.cpp go further — 100% schema compliance at the token level. Methods ranked by reliability, with working code examples.
Local AI for Privacy: What's Actually Private
Running AI locally keeps prompts off corporate servers — but model downloads, telemetry, and VS Code extensions can still leak data. Here's what's genuinely private, what isn't, and how to close every gap.
Best Local LLMs for Summarization
Qwen 2.5 14B is the summarization sweet spot — strong instruction following, 128K context for 200-page docs, fits on 16GB VRAM. Model picks by use case, quality ratings, chunking strategies, and prompting tips.
Managing Multiple Models in Ollama: Disk Space, Switching, and Organization
Five 7B models eat 20GB before you notice. Check what's using space with ollama list, clean up with ollama rm, and set OLLAMA_KEEP_ALIVE to control memory. A practical cleanup and organization guide.
Best Vision Models You Can Run Locally: Every Model, Every GPU Tier (2026)
Qwen3-VL 8B replaced Qwen2.5-VL as the best local vision model. Full VRAM table, Ollama commands, speed benchmarks, and setup for every GPU from 4GB to 48GB+. Updated March 2026.
Best Local LLMs for RAG in 2026
The best local models for retrieval-augmented generation by VRAM tier. Qwen 3, Command R 35B, embedding models, and RAG stacks with real failure modes.
Fix OpenClaw Token Waste: $150 to $6 Overnight
Cut OpenClaw API costs by 97% with three proven fixes: route heartbeats through Ollama, add tiered model routing, and purge session history token bloat.
Best Local LLMs for Mac in 2026 — M1, M2, M3, M4 Tested
The best models to run on every Mac tier. Specific picks for 8GB M1 through 128GB M4 Max, with real tok/s numbers. MLX vs Ollama vs LM Studio compared.
Stop Using Frontier AI for Everything
Build a tiered AI model strategy that stops wasting money on GPT-4 and Claude Opus. Route tasks to local models, Haiku, Sonnet, or Opus based on complexity.
Mac Runs 70B Models That Need Multi-GPU on PC — Here's How
Your M4 Max loads models that cost $3,000 in GPUs on PC. M1 with 8GB handles 7B, M4 Pro with 48GB runs 32B, and 128GB loads 70B+. MLX vs Ollama speeds tested, plus Mac Mini as a 24/7 AI server.
Local AI Troubleshooting Guide: Every Common Problem and Fix
Model running 30x slower than expected? Probably on CPU instead of GPU. Fixes for won't-load errors, CUDA crashes, garbled output, and OOM across Ollama and LM Studio.
Fastest Local LLM Setup: Ollama vs vLLM vs llama.cpp Real Benchmarks
vLLM handles 4x the concurrent load of Ollama on identical hardware. But for single-user local use, Ollama is all you need. Benchmarks, memory usage, and a dead-simple decision framework. Updated for Ollama v0.17.7, vLLM v0.17.0, and llama.cpp with MCP support.
Best Local Models for OpenClaw Agent Tasks
Qwen 3.5 27B on 24GB VRAM is the sweet spot for local agents — SWE-bench 72.4, 262K context, tool calling fixed in Ollama v0.17.6+. Model picks by VRAM tier and the 'society of minds' setup power users run.
Are Mistral Models Still Worth Running? Only Nemo 12B (Here's Why)
Mistral led local AI in 2024. In 2026, Qwen 3 and Llama 3 have passed them on most benchmarks. The exception: Mistral Nemo 12B with 128K context still earns its slot. What's worth running, what's been replaced, and when to pick Mistral over the competition.
Open WebUI Setup Guide: ChatGPT UI for Local AI
1 Docker command gives you a ChatGPT-like interface for any Ollama model. 120K+ GitHub stars, built-in RAG, voice chat, and multi-model switching—all running locally.
Llama 3 Guide: Every Size from 1B to 405B
Complete Llama 3 guide covering every model from 1B to 405B. VRAM requirements, Ollama setup, benchmarks vs Qwen 3, and which size fits your hardware.
DeepSeek Models Guide: R1, V3, and Coder
Complete DeepSeek models guide covering R1, V3, and Coder locally. Which distilled R1 to pick for your GPU, VRAM requirements, and benchmarks vs Qwen 3.
Best Way to Set Up OpenClaw (2026 Guide)
Run `npx openclaw@latest`, scan a QR code for WhatsApp, and your AI agent is live. Gateway needs just 2-4GB RAM. Add Ollama for local models or connect Claude/GPT-4 via API.
Best Qwen Models Ranked: Which to Run Locally
Complete Qwen models guide covering Qwen 3.5, Qwen 3, Qwen 2.5 Coder, and Qwen-VL. VRAM requirements, Ollama setup, Gated DeltaNet architecture, and benchmarks vs Llama and DeepSeek.
Best Local LLMs for Math & Reasoning: What Actually Works
The best local LLMs for math and reasoning tasks, ranked by VRAM tier. AIME and MATH benchmarks for DeepSeek R1, Qwen 3 thinking, and Phi-4-reasoning.
LM Studio Tips & Tricks: Hidden Features
Speculative decoding for 20-50% faster output, MLX that's 21-87% faster on Mac, a built-in OpenAI-compatible API, and the GPU offload settings most users miss.
Ollama Troubleshooting Guide: Every Common Problem and Fix
GPU not detected? Running at 1/30th speed on CPU? OOM crashes mid-generation? Every common Ollama error with exact diagnostic commands and fixes for Mac, Windows, and Linux. Updated for v0.17.7 and Qwen 3.5.
Best Local LLMs for Chat & Conversation
The best local LLMs for chat and conversation in 2026. Picks for every VRAM tier from 8GB to 24GB, with Ollama commands to start chatting immediately.
Run Your First Local LLM in 15 Minutes
Install Ollama, pull a model, and chat with AI offline—all in 15 minutes. Works on any Mac, Windows, or Linux machine with 8GB RAM. No accounts, no API keys, no fees.
Ollama vs LM Studio: Speed, Setup, and Verdict
Ollama gives you a CLI with 100+ models and an OpenAI-compatible API. LM Studio gives you a visual GUI with one-click downloads. Most power users run both—here's when to use each.