Local AI Models Tutorials
Running open-weight models locally with Ollama and picking the right model for your hardware.
OmniRoute Setup on Mac: Connect Claude Code for Free AI Tokens
earn how to install and configure OmniRoute on macOS to route Claude Code through free AI model endpoints and avoid token rate limits. Complete Terminal guide. <p class="lead">OmniRoute is an open-source local AI gateway that lets you aggregate free-tier provider models behind a single OpenAI-compatible endpoint. Follow this step-by-step guide to install OmniRoute on macOS and integrate it with Claude Code to bypass usage limits.</p> <h2>Prerequisites</h2> <ul> <li>A Mac running macOS Big Sur or newer (Intel or Apple Silicon M1/M2/M3/M4)</li> <li>Node.js (v18 or higher recommended)</li> <li>Terminal app (or iTerm2)</li> </ul> <h2>Step 1: Install OmniRoute Globally on Mac</h2> <p>Open your macOS Terminal and execute the global npm installation command:</p> <code>npm i -g omniroute</code> <h2>Step 2: Start the OmniRoute Service</h2> <p>Launch the OmniRoute gateway server locally:</p> <code>omniroute</code> <p>This starts the gateway on your local machine (defaulting to port 20128) and prints the local dashboard URL: http://localhost:20128.</p> <h2>Step 3: Connect Free Providers in the Dashboard</h2> <ol> <li>Open http://localhost:20128 in your browser.</li> <li>Navigate to the Providers tab.</li> <li>Connect your preferred free-tier API providers (such as Gemini, Groq, Kimi, GLM, or DeepSeek).</li> <li>Go to the API Keys section and generate a local token for authentication.</li> </ol> <h2>Step 4: Configure Claude Code to Route Through OmniRoute</h2> <p>To direct Claude Code CLI traffic through your local OmniRoute instance, set the Anthropic environment variables in your active shell or ~/.zshrc file:</p> <code>export ANTHROPIC_BASE_URL="http://localhost:20128"</code><br> <code>export ANTHROPIC_AUTH_TOKEN="your_omniroute_api_key"</code><br> <code>export CLAUDE_CODE_ENABLE_GATEWAY_MODEL_DISCOVERY=1</code> <h2>Step 5: Verify the Connection</h2> <p>Run a test query in Claude Code to verify requests are reaching your gateway:</p> <code>claude "Hello, confirm connection status."</code> <h2>Useful Resources</h2> <ul> <li><a href="https://github.com/diegosouzapw/OmniRoute" target="_blank" rel="noopener">OmniRoute Official GitHub Repository</a></li> <li><a href="https://nodejs.org/" target="_blank" rel="noopener">Download Node.js for Mac</a></li> <li><a href="https://docs.anthropic.com/en/docs/agents-and-tools/claude-code/overview" target="_blank" rel="noopener">Claude Code Official Documentation</a></li> </ul>
Use GPT 6 Astra FREE in Codex (Free Unlimited Codex with GPT 6)
In this video, I'm walking you through how to set up and configure the GPT-6 Astra model with your local development environment using Flagship Router. This is an educational tutorial about local model configuration and development tool management—all standard practices that developers use for their workflows. 📌 What This Video Covers: Cloning the Flagship Router repository from the official source Installing Node.js and project dependencies with npm install Running the launch command to build and start the local router Logging into the Flagship Router web interface Turning off the API key requirement for smoother operation Exploring the model library—336 models available with 86 ready to use Finding and testing the GPT-6 Astra model Copying the model identifier for configuration Using the CLI Tools section to configure your development application Applying the model configuration and launching your app Verifying the setup with a live test prompt Confirming the connection through Flagship Router ⚙️ How It Works: Flagship Router is a local routing tool that helps developers manage connections between their coding applications and various model providers. In this tutorial, I demonstrate how to configure it with the GPT-6 Astra model and integrate it with development tools using standard local proxy techniques. 🛠️ Prerequisites: Node.js installed on your system Git installed for cloning the repository Basic familiarity with terminal or command prompt A development application or code editor installed 🔗 Resources Mentioned: Flagship Router Repository: https://github.com/theRizwan/FlagshipRouter Node.js Official Website: https://nodejs.org 📝 Disclaimer: This video is for educational and informational purposes only. It demonstrates standard local development environment configuration techniques using open-source tools and models. The tools and methods shown are intended for personal learning and legitimate development workflows. Always ensure you comply with the terms of service of any software or platform you use. 💬 Have questions about the setup or ran into an issue? Drop a comment below and I'll personally help you out. 🔔 Subscribe to Rizwan for more coding tutorials, development environment setups, and tech guides every week. #GPT6Astra #FlagshipRouter #LocalDevelopment #CodingSetup #AIModels #ProgrammingTutorial #Rizwan
I Tested 1B-1.7B AI Models Locally — Here Is What Happened
I ran Claude on 1B–1.7B local AI models to see if they could actually handle coding tasks on my 24GB RAM machine. Testing small language models is the best way to understand the limits of local hardware. Monitoring system performance while pushing these tiny models to their breaking point reveals if they can maintain efficiency without killing CPU or memory resources. Whether you are using a Claude coding agent or exploring general LLM inference, knowing which model size fits your specific setup is key. The results from these tests highlight which configurations work and where the performance falls off. Subscribe for weekly AI performance breakdowns, and let me know in the comments if you want to see a test with larger parameter sizes next.
Get 7.4 Billion Free AI Tokens/Month from FreeLLMAPI (Claude Free LLM API Setup)
FreeLLMAPI gives you a free LLM API endpoint you can plug straight into Claude — no credit card, no subscription. In this video I walk through the full setup, step by step, from getting your key to pointing your coding agent at it. Most "free AI API" videos stop at the signup link. This one shows the part that actually breaks: wiring the endpoint into your agent config, handling model routing, and getting your first real completion out the other end. ⏱️ TIMESTAMPS 0:00 — What FreeLLMAPI actually gives you 0:00 — Getting your free API key 0:00 — Configuring Claude to use it 0:00 — Model routing setup 0:00 — Testing it live 0:00 — Limits, rate caps, and what to watch for 🔗 LINKS FreeLLMAPI: https://github.com/tashfeenahmed/freellmapi Free AI Server: https://youtu.be/H0qB5P20Ay0 More free AI coding agent setups on the channel — Claude and local model routing. #FreeLLMAPI #Claude #FreeAIAPI #AICoding #ClaudeAPI make sure to change the device name as well as user and the unified api key { "deploymentMode": "3p", "coworkUserFilesPath": "C:\\Users\\HP\\Claude", "preferences": { "coworkBrowserToolsEnabled": true, "launchPreviewPersistedWorkspaces": [], "launchPreviewSessionScopedSessions": [], "remoteFolderConsentMemory": [], "coworkLegacyRootGrantsPruned": true, "coworkScheduledTasksEnabled": true, "orgWorkAcrossAppsDisabled": false, "ccdScheduledTasksEnabled": true, "earlyWindowShowLatched": true, "sidebarMode": "chat", "bypassPermissionsGateByAccount": { "84903b34-ef23-4c45-9f8c-6ab0c6e9c9eb": false }, "coworkWebSearchEnabled": true, "coworkModelAutoFallbackByAccount": { "84903b34-ef23-4c45-9f8c-6ab0c6e9c9eb": true }, "remoteToolsDeviceName": "desktop-2fcsr34", "epitaxyPrefs": { "starred-local-code-sessions": [], "starred-cowork-spaces": [], "starred-session-groups": [], "dframe-group-scopes": {}, "dframe-local-slice": { "pinnedOrder": [], "homeProjectsPinnedOrder": [] }, "ccd-sessions-filter": { "state": { "selectedProjects": [] }, "version": 0 }, "mcpServers": { "vidiq": { "command": "npx", "args": [ "-y", "@vidiq/mcp-server" ] }, "omniroute": { "command": "omniroute", "args": [ "--mcp" ] } }, "desktop-frame.paneStore.v1": { "state": { "extraPanesByMode": {}, "colWeightsByMode": {}, "rowSplit": 0.5, "draftNonce": 0, "lastPrimaryCodeSession": null }, "version": 4 }, "starred-local-routines": [] }, "mcpServers": { "freellmapi": { "command": "npx", "args": [ "-y", "@modelcontextprotocol/server-fetch" ], "env": { "ANTHROPIC_BASE_URL": "http://localhost:3001", "ANTHROPIC_AUTH_TOKEN": "" } } }, "coworkHipaaRestricted": false } }
Don't Buy a GPU: Build This 32GB Free AI Server Instead ($0 Cost)
What if you could run a 27B AI model with almost 32GB of GPU VRAM — completely FREE? 🤯 In this video, I’m building a powerful AI inference server using 2× Tesla T4 GPUs and Ollama, then using it to run a 27B parameter model. We’ll go from a fresh Kaggle environment to a fully working AI server and test the model with real AI coding workflows. 🔥 What you'll learn in this video: • How to get access to 2× Tesla T4 GPUs • How to set up Ollama for multi-GPU inference • How to run a 27B Q4 AI model • How to configure a 64K context window • How to create and use an MTP model • How to keep the model loaded in GPU VRAM • How to check GPU usage with NVIDIA-SMI • How to benchmark AI generation speed • How to expose your Ollama server through a temporary public API • How to connect the server with Hermes Agent • How to connect it with OpenCode • How to use your remote GPU server for real AI coding workflows 📌 TIMELINE: 00:00 – What We’re Building 01:36 – Setup Kaggle & Import the Notebook 04:46 – Install Ollama & Run the 27B Model 05:23 – MTP, GPU Load & Benchmark 06:00 – Cloudflare + OpenCode 🚀 MODEL USED Qwen3.8 27B Uncensored Q4_K_M ⚡ STACK USED • Ollama • Kaggle GPU • 2× NVIDIA Tesla T4 • MTP • Cloudflare Tunnel • Hermes Agent • OpenCode 📓 GET THE NOTEBOOK https://drive.google.com/file/d/1whN2AAkQ0GGUTYeLOAsbYcShx-DMTdMj/view?usp=sharing ⚠️ IMPORTANT The GPU availability and session limits depend on the platform and may change over time. This setup uses a temporary GPU environment, so it is not a permanent cloud server. 1. Check GPU Run this after selecting GPU in Kaggle settings: !nvidia-smi If you see NVIDIA GPU details, the GPU is active. ________________________________________ 2. Install Zstandard Ollama’s installer may need zstd to extract its download. !sudo apt-get update -y !sudo apt-get install -y zstd ________________________________________ 3. Install Ollama !curl -fsSL https://ollama.com/install.sh | sh ________________________________________ 4. Confirm Ollama Installation !ollama --version You should see an Ollama version number. ________________________________________ 5. Start Ollama Server Run this in a Python code cell: import subprocess import time ollama_process = subprocess.Popen( ["ollama", "serve"], stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL ) time.sleep(5) print("Ollama started") ________________________________________ 6. Confirm Ollama Is Running !curl http://127.0.0.1:11434 Expected result: Ollama is running ________________________________________ 7. Download the AI Model !ollama pull qwen3.8:latest Wait for the download to finish completely. ________________________________________ 8. Check the Installed Model Name !ollama list You should see: qwen3.8:latest Use this exact name in all later commands and in VS Code. ________________________________________ 9. Test the Model Locally Run this in a Python code cell: import requests response = requests.post( "http://127.0.0.1:11434/api/generate", json={ "model": "qwen3.8:latest", "prompt": "Reply with exactly: Tech2AI model test successful.", "stream": False }, timeout=300 ) print("Status:", response.status_code) print(response.text) A successful response should show: Status: 200 Tech2AI model test successful. ________________________________________ 10. Install Cloudflared !wget -q https://github.com/cloudflare/cloudflared/releases/latest/download/cloudflared-linux-amd64.deb !sudo dpkg -i cloudflared-linux-amd64.deb ________________________________________ 11. Confirm Cloudflared Installation !cloudflared --version You should see a Cloudflared version number. ________________________________________ 12. Create the Cloudflare Tunnel Run this in a Python code cell: import subprocess import time cloudflared = subprocess.Popen( [ "cloudflared", "tunnel", "--url", "http://127.0.0.1:11434", "--http-host-header", "localhost:11434" ], stdout=subprocess.PIPE, stderr=subprocess.STDOUT, text=True ) time.sleep(8) for _ in range(30): line = cloudflared.stdout.readline() if line: print(line, end="") Wait for a temporary URL like this: https://something-random.trycloudflare.com Copy that URL. Important: Keep this cell running. If you stop it, the public tunnel will stop working. ________________________________________ 13. Test the Public Tunnel Replace the sample URL with your actual tunnel URL: import requests PUBLIC_URL = "https://your-tunnel.trycloudflare.com" response = requests.get(PUBLIC_URL + "/api/tags", timeout=60) print("Status:", response.status_code) print(response.text) If you see status 200 and the model list, the tunnel is working. ________________________________________ 14. Cline Settings in VS Code Open VS Code → open/install Cline → select OpenAI Compatible as API Provider. #AI #Ollama #Kaggle #LocalAI #LLM #AICoding #OpenSourceAI #HermesAgent #OpenCode #GPU #TeslaT4
I Ran Claude Code With a 0.5B Local AI Model: Does It Actually Work?
I ran Claude Code with a 0.5B local AI model on a 24GB RAM laptop to see if it actually works. In this video I test tiny local LLMs on real coding tasks and show exactly what works, what breaks, and what I'd use instead. Can a 0.5B model handle tool calling, file edits, and code generation inside Claude Code? Watch the full test to find out. ⏱️ CHAPTERS 0:00 Does Claude Code work with a 0.5B local model? 0:30 My laptop and setup (24GB RAM) [0:00] How I connected local models to Claude Code [0:00] Test 1: [task, e.g. write a function] [0:00] Test 2: [task, e.g. fix a bug] [0:00] Test 3: [task, e.g. create and edit files] [0:00] Results: what worked and what failed [0:00] Which local model size I recommend 🛠️ WHAT I USED Laptop: 24GB RAM [CPU/GPU model] Runner: [Ollama / LM Studio / other] Models tested: [model names and sizes] Setup commands and config: [link to your devnesthub.com post] 📌 KEY TAKEAWAY [One sentence verdict, e.g. "0.5B can chat and write simple code, but struggles with Claude Code's tool calling. 3B-7B is the realistic minimum."] ▶️ WATCH NEXT [Link to your next related video] Subscribe for more local AI, Claude Code, and developer tutorials. #ClaudeCode #LocalAI #Ollama #LocalLLM #AICoding
I Tested a 100M AI Model on a 24GB RAM Laptop
How small can an AI model actually be? In this video, I test a **100 million parameter AI model** on my **24GB RAM laptop** to see how well it performs, how much memory it uses, how fast it responds, and—most importantly—whether a model this small is actually useful. This is Episode 1 of a series where I test AI models from the smallest to the largest. We're starting at just **100M parameters** and eventually working our way up to much larger models to find out exactly how far a 24GB RAM laptop can go. In this episode, I test: • 100M parameter AI model • Local AI performance • RAM usage • Response speed • Real-world prompts • Model quality • Whether it's actually useful • How a tiny model compares to larger AI models The goal isn't just to see whether the model runs. **The goal is to find out what you actually get when you go this small.** And this is only the beginning. 100M → 300M → 500M → 1B → 3B → 7B → 14B → and beyond. Subscribe if you want to follow the entire experiment. #AI #LocalAI #Ollama
GLM 5.3 & DeepSeek 4.1 for Free (100% working,No ClickBait)
Want to try GLM-5.3 & DeepSeek 4.1 for free In this video, I'll show you how to access GLM-5.3 & deepseek v 4.1, get the available free token , and set everything up step by step. We'll go through the setup process and test the model to see how it performs with real AI tasks. Website link - https://www.verdent.ai/ What You'll Learn: How to access GLM-5.3 How to access deepseev-4.1 How to get millions free tokens How to set up GLM-5.3 How to set up DeepSeek 4.1 How to use GLM-5.3 for AI tasks How to use deepseek 4.1 for AI tasks How to test GLM-5.3 How to test deepseek How to use GLM models through an API How to use deepseek models through an API How to use free AI tokens by the end watch results of both the models glm 5.3 and deepseek v 4.1 If you're looking for a powerful AI model to experiment with without immediately paying for API usage, this setup can be a useful option. timestamps: 00:00 Introduction 00:06 Downloading Warden AI 00:27 Account Creation & Installation 00:59 App Configuration & Workspace Setup 01:44 Enabling Free Models (GLM 5.3 & DeepSeek 4.1) 02:05 Usage Limits Explained 02:23 Testing GLM 5.3 (Creating 3D Web Page) 02:53 Reviewing GLM 5.3 Output 03:30 Testing DeepSeek 4.1 03:56 Reviewing DeepSeek Output & Comparison 04:22 Conclusion & Outro Subscribe to Web Tech Knowledge for more AI, Linux, programming, and technology tutorials. 🤖🐧 #GLM53 #GLM5 #AI #FreeAITokens #AIAgent #LLM #ArtificialIntelligence #deepseek #deepseek4.1 GLM 5.3,deepseek 4.1, GLM-5.3, deepseek-4.1,GLM 5, deepseek 4, GLM5, GLM AI, GLM model, GLM 5.3 free, GLM 5.3 free tokens, 100 million free tokens, 100m free tokens, free AI tokens, GLM API, GLM 5.3 API, GLM API tutorial, GLM 5.3 tutorial, GLM AI tutorial, free AI API, free AI, AI model, LLM, large language model, AI tools, free LLM, GLM 5.3 2026
Kilo Code Setup: FREE AI Models for Unlimited AI Tokens (2026 Full Guide)
Kilo Code Setup: FREE AI Models for Unlimited AI Tokens (2026 Full Guide) Kilo Code gives you free AI models inside VS Code — no credit card, no API key, and no subscription. In this video I show the full Kilo Code setup from scratch, how to find the free models in the model picker, and how to actually use them for real coding work without burning through paid tokens. Kilo Code is an open-source AI coding agent (VS Code, JetBrains, and CLI) with access to 500+ models. The part most people miss: a chunk of those models are listed at $0 input and $0 output pricing, so you can run agentic coding, refactors, and debugging all day for free. ⏱️ TIMESTAMPS 00:00 - Why paid AI coding tools are draining your wallet 00:45 - What Kilo Code actually is 01:30 - Installing Kilo Code in VS Code 02:40 - Creating your free Kilo account (no credit card) 03:50 - Finding the FREE models in the model picker 05:10 - Best free models right now + which to pick 07:00 - Code / Architect / Ask / Debug modes explained 09:15 - Building a real project with free models 12:30 - BYOK: connecting OpenRouter, Ollama & LM Studio 14:20 - Rate limits & the honest catch 16:00 - Tips to make free models perform like paid ones 18:00 - Final thoughts 🔗 LINKS Kilo Code: https://kilo.ai VS Code Marketplace: https://marketplace.visualstudio.com/items?itemName=kilocode.Kilo-Code Live free model list: https://kilo.ai/landing/free-models 🧠 FREE MODELS COVERED NVIDIA Nemotron 3 Ultra (free), MiniMax M2.7 & M3 (free), Ling 3.0 Flash + Flash VL (free), Nex-N2.5 Pro (free), Tencent Hy3 (free), Ring-2.6-1T (free), Poolside Laguna S 2.1 (free), Dots3-Note Preview (free) ❓ FAQ Is Kilo Code really free? The extension is open source and free. Models marked "Free" in the picker have $0 token pricing — you only pay if you choose a paid model. Do I need an API key? No. Create a Kilo account and the free models work instantly. You can still bring your own key if you prefer. Does it work in JetBrains? Yes — VS Code, JetBrains IDEs, and a CLI. Will the free models stay free? Free hosted models are provider promotions and the list changes. Check the live catalog link above. ⚠️ Heads up: free model availability rotates as providers change pricing. What's free in this video may differ by the time you watch — the model picker always shows current pricing. 👍 If this saved you a subscription, drop a like and subscribe for more AI dev workflow videos. #KiloCode #AICoding #VSCode #FreeAI #VibeCoding What is Kilo Code? Is Kilo Code free? How do I install Kilo Code? What IDEs and platforms does Kilo support? Which AI models does Kilo Code support? How does pricing work and can I bring my own API key? How does Kilo handle code privacy and data? What agent modes does Kilo Code have? How do Cloud Agents work? Does Kilo understand my entire codebase? What programming languages does Kilo support? Why switch from Cursor to Kilo Code? How does Kilo Code compare to GitHub Copilot? Does Kilo support MCP (Model Context Protocol)? Can I use Kilo Code on a team or in an enterprise? Is Kilo Code really open source?
Install OmniRoute Setup in Claude for FREE Unlimited AI Tokens (Full Install Guide)
Install OmniRoute Setup in Claude for Free AI Tokens in under 10 minutes — completely free. This OmniRoute setup guide (2026 update) walks through the full install, connecting free providers, pointing Claude at your local gateway, and fixing the errors most people hit. OmniRoute is a free, MIT-licensed, open-source AI gateway that runs locally on your machine. It gives you one OpenAI-compatible endpoint that routes across 350+ providers and 1200+ models — Claude, GPT, Gemini, Kimi, DeepSeek, GLM, MiniMax and more — with automatic fallback when a provider rate-limits you. That means when your Claude quota runs dry, your request silently reroutes instead of failing. In this complete OmniRoute tutorial you'll learn how to install OmniRoute with a single npm command , how to use the keyless quick start with no credit card, how to connect free-tier providers in the OmniRoute dashboard, how to configure Claude to use your local OmniRoute endpoint, how to verify everything works with a live test request, and how to set up auto-fallback so you never hit a rate limit mid-task. Same setup also works for Claude Desktop, Codex CLI, Cursor, Cline, Roo Code, Goose and any other OpenAI-compatible tool — I show the config for each at the end. Whether you searched for "omniroute setup", "omniroute claude", "how to install omniroute", "omniroute claude code setup", "omni route claude", or "omniroute codex" — this video covers all of it in one place. ⏱️ Timestamps 00:00 What OmniRoute is and why it beats a single API key 00:40 What's new in OmniRoute (2026 update) 01:20 How to install OmniRoute (npm,source) 03:00 Keyless quick start — no credit card, no API key 04:10 Connecting free providers in the OmniRoute dashboard 05:40 How to configure Claude Code to use OmniRoute 07:00 Claude Desktop, Codex, Cursor & Cline configs 🔗 Links OmniRoute GitHub —https://github.com/diegosouzapw/OmniRoute OmniRoute dashboard / quickstart https://github.com/diegosouzapw/OmniRoute#-quick-start Claude Code docs https://code.claude.com/docs/en/overview OmniRoute setup video https://youtu.be/3gbyqBMlAWM ❓ Stuck on a step? Drop a comment with the exact error text and I reply to every one. #OmniRoute #ClaudeCode #FreeAI
Ollama Tutorial: Run Local AI Models + Ollama Cloud Setup (Full Guide)
Learn how to set up Ollama and run local AI models on your own computer, plus how to use Ollama Cloud models when you need more power than your GPU can handle. This step-by-step Ollama tutorial covers installation on Windows, macOS and Linux, pulling and running models, switching between local and cloud models, and connecting Ollama to your own apps through its API. Ollama lets you run open-source LLMs like Llama, Gemma, Qwen and DeepSeek completely offline and private — no subscription and no data leaving your machine. Ollama Cloud runs the same models on remote hardware using the exact same commands, so you can run large models that won't fit on a laptop. ⏱️ TIMESTAMPS 00:00 Intro — what Ollama is and why use it 00:20 Installing Ollama (Windows / Mac / Linux) 00:40 Running your first local AI model 01:00 Choosing the right model for your hardware (RAM & VRAM) 01:20 Essential Ollama commands (pull, run, list, rm, ps) 01:30 Ollama Cloud models — signing in and running them 01:40 Local vs cloud: when to use which 02:30 Using the Ollama API + API keys 03:00 Connecting Ollama to other tools 03:15 Troubleshooting common errors 03:30 Final thoughts ❓ QUICK ANSWERS What is Ollama? Ollama is a free tool that downloads and runs open-source large language models locally on your own computer through a simple command line or API. Is Ollama free? Yes, Ollama and local models are free. Cloud models require a free ollama.com account, with usage limits on the free tier. What are Ollama Cloud models? Cloud models look and behave like local models, but the work is offloaded to Ollama's servers, so you can run large models without a powerful GPU. Do I need a GPU for Ollama? No. Small models (1B–8B) run on CPU and 8–16 GB of RAM, though a GPU makes them much faster. For big models, use cloud models. Is Ollama private? Local models run fully offline and nothing is sent anywhere. Cloud models send your prompts to Ollama's servers, and Ollama can be locked to local-only mode if you prefer. 🔗 LINKS Ollama download: https://ollama.com/download Model library: https://ollama.com/search Docs: https://docs.ollama.com 👍 If this helped, like and subscribe for more local AI and self-hosted AI tutorials. #ollama #localai #llm #aimodels #ollamacloud
Gemini 3,GLM 5.3,Ling 3.0,Qwen 3.8,Mistral Large 3 & More — 100% FREE Forever 🤯
Want to use Gemini 3, GLM 5.3, Ling 3.0, Qwen 3.8, Mistral Large 3 and 20+ more AI models for 100% FREE? No credit card, no subscription — here's exactly how. In this video I show you a full list of free AI models you can access right now, including models with up to 1 MILLION token context windows. I'll walk you through where to find them, how to get an API key, how to compare speed and uptime, and which free models are actually worth using for coding, writing, image generation and reasoning. Whether you're a developer building side projects, a student who can't afford ChatGPT Plus, or you just want to test the newest models before paying for them, this list will save you hundreds of dollars. ⏱️ TIMESTAMPS 00:00 – Intro: 20+ free AI models 00:xx – Where to find these free models 00:xx – How to get your free API key 00:xx – Best free model for coding 00:xx – Best free model for reasoning 00:xx – Free image generation models 00:xx – Models with 1M context window 00:xx – Speed & uptime comparison 00:xx – Which one should you use? 🔗 LINKS Free models list: [your link] My other AI videos: [playlist link] ❤️ If this helped, drop a LIKE and SUBSCRIBE — I post free AI tools and API tutorials every week. Note: free tiers can change at any time, so check current limits before you build on them. #FreeAI #Gemini3 #AITools
Freebuff: The FREE Claude Code Alternative? (2026)
Freebuff is a powerful FREE AI coding agent and a potential alternative to Claude Code. In this video, I'll show you how to install Freebuff, set it up, and use it for AI-powered coding in your terminal. You'll see how Freebuff works, which AI models are available, and how its free AI coding experience compares with tools like Claude Code and other AI coding agents. Topics covered: Freebuff setup 2026 Freebuff installation Free AI coding agent Free Claude Code alternative Freebuff AI models MiniMax M2.7 AI coding in terminal Free coding agent Claude Code alternative AI programming tools 2026 Free AI developer tools If you're looking for a free AI coding agent that can help you write, modify, debug, and understand code, Freebuff is worth checking out.
Claude Code + VS Code: Free AI Coding Setup (2026 Guide)
Set up Claude Code in VS Code for free in under 10 minutes. Install, authenticate, configure CLAUDE.md, and add a local fallback for unlimited coding. H1: How to Set Up Claude Code in VS Code for Free. Claude Code runs inside VS Code through Anthropic's official extension. Install Node.js, add the Claude Code extension from the VS Code Marketplace, sign in with a free Anthropic account, and open the panel with the keyboard shortcut. Setup takes about five minutes and requires no paid subscription to start. H2: What is Claude Code for VS Code? H2: Is Claude Code free to use in VS Code? H2: How do you install the Claude Code extension? (numbered steps, one action per step) H2: What are the system requirements? H2: How do you get better results with a CLAUDE.md file? H2: How do you run a free local model as a fallback? H2: Claude Code vs Cursor vs GitHub Copilot: which is free? (comparison table — tables get cited heavily in AIOs) H2: Common setup errors and fixes H2: Frequently asked questions FAQ block (mark up with FAQPage schema): Is Claude Code free? — There is a free tier with usage limits, plus the VS Code extension itself is free. Heavier daily use generally requires a paid plan or API credits. Do I need the terminal? — No. The extension gives you a full GUI panel, though the CLI remains available. Does it work offline? — Not on its own. Pair it with a local model runner like Ollama for offline coding. Which languages does it support? — Any language VS Code supports; results are strongest in widely-used ecosystems like Python, JavaScript, TypeScript, and Go.
Use Codex for FREE with Ollama — $0 AI Coding
Can you use Codex for free with local AI models? In this video, I'll show you how to connect Codex with Ollama and use local AI models for coding without relying entirely on paid cloud AI APIs. You'll see the complete setup, how the workflow works, and how Codex can interact with local models through Ollama. You'll learn: • How to use Codex for free • How to install and configure Ollama • How to connect Codex with local AI models • How to run AI coding models locally • How to use Ollama models for coding • Whether this setup can reduce AI API costs • What limitations you should know about • How to choose a local model for coding ### Is Codex free? Codex availability and usage limits depend on the specific Codex product, account, and access method. This tutorial focuses on using Codex together with local AI models through Ollama to explore a $0-cost local AI coding workflow. ### What is Ollama? Ollama allows AI models to run locally on your own computer. Instead of sending every request to a cloud API, compatible models can run directly on your machine. ### Codex + Ollama The interesting part is combining an AI coding workflow with local models. This can give developers another option when they want to experiment with AI coding without continuously paying for API usage. Watch the complete tutorial to see the setup and test the workflow yourself. #Codex #Ollama #AICoding #LocalAI #OpenAI #Coding Is Codex free? How do I use Codex for free? Can Codex use local AI models? Can I use Ollama with Codex? How do I connect Codex to Ollama? Can Ollama be used for coding? What is the best local AI model for coding? Can I run AI coding models locally? How can I code with AI for free? Can local AI replace paid coding APIs?
What Is OpenClaw? The Free AI Assistant That Actually Does Things
H1: OpenClaw: The Free AI Agent That Actually Does Things OpenClaw is a free, open-source AI agent created by Peter Steinberger that runs locally on your own computer and takes instructions through chat apps you already use — WhatsApp, Telegram, Signal, Discord, or iMessage. Released in November 2025, it is now the most-starred repository on GitHub with over 388,000 stars, surpassing Linux and React. H2: What is OpenClaw and who made it? Cover Peter Steinberger (Austrian developer, founder of PSPDFKit), November 2025 release, MIT license, TypeScript and Swift, cross-platform. H2: Why was OpenClaw renamed from Clawdbot to Moltbot to OpenClaw? This is a genuinely high-volume query with a clean factual answer: Clawdbot (Nov 2025) → Moltbot on January 27, 2026 after trademark complaints from Anthropic over the similarity to Claude → OpenClaw on January 30, 2026, because Steinberger said Moltbot "never quite rolled off the tongue." Include the dates. Date-anchored facts get cited heavily. H2: What can OpenClaw actually do? Ground the "actually does things" claim in concrete verbs: organizes inboxes, sends email, manages calendars, checks you in for flights, runs cron jobs and scheduled heartbeats, keeps persistent local memory across sessions, writes and installs its own skills. Persistent memory is the differentiator most comparison queries hinge on. H2: Is OpenClaw really free? Yes for the software, no for the intelligence. Explain the token cost, and that you can sign in with an existing ChatGPT or Claude subscription, or route to DeepSeek or a local model. H2: How do you install OpenClaw? Desktop apps for macOS, Windows and Linux, or npm install -g openclaw with Node.js 22+, then the onboarding wizard. Realistic time estimate: 15 minutes, not 5. H2: Is OpenClaw safe to use? Do not skip this or soften it. Pages that only sell OpenClaw get outranked in AI answers by pages that address risk, because the risk queries have enormous volume. Cite Cisco's finding that a third-party skill performed data exfiltration and prompt injection without user awareness, the published one-click RCE and command-injection advisories, Axios and IBM X-Force coverage, and the maintainer quote that if you can't use a command line "this is far too dangerous of a project for you to use safely." Then give mitigations: run it in a sandbox or VM, use Microsoft Execution Containers on Windows, scope credentials narrowly, never expose the gateway to the open internet, vet skills manually. H2: OpenClaw vs Claude Code vs ChatGPT agents Put this in an actual HTML table with rows for interface, memory, autonomy, cost model, and license. Tables are disproportionately likely to be parsed into comparison answers. H2: Who owns OpenClaw now? On February 15, 2026 Sam Altman confirmed OpenAI acquired OpenClaw and Steinberger joined the company; the project moved to a foundation to remain open and independent. This is the freshest major development and a strong differentiator versus older articles still ranking. H2: FAQ { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [ { "@type": "Question", "name": "Is OpenClaw free?", "acceptedAnswer": { "@type": "Answer", "text": "OpenClaw is free and open source under the MIT license. However, it requires a large language model to function, so you pay for API tokens from providers like Anthropic, OpenAI, or DeepSeek, or connect an existing ChatGPT or Claude subscription. Running a local model makes it fully free." } }, { "@type": "Question", "name": "How many GitHub stars does OpenClaw have?", "acceptedAnswer": { "@type": "Answer", "text": "OpenClaw has over 388,000 GitHub stars and roughly 3,300 contributors, making it the most-starred software repository on GitHub, ahead of Linux and React. It reached that position in under six months from its November 2025 release." } }, { "@type": "Question", "name": "Is OpenClaw safe?", "acceptedAnswer": { "@type": "Answer", "text": "OpenClaw carries real security risks because it requires broad permissions to email, calendars, files, and messaging accounts. Documented issues include prompt injection, malicious third-party skills, and a one-click remote code execution advisory. Cisco researchers found a community skill exfiltrating data without user awareness. Run it sandboxed, scope credentials narrowly, and never expose the gateway to the public internet." } }, { "@type": "Question", "name": "What was OpenClaw called before?", "acceptedAnswer": { "@type": "Answer", "text": "OpenClaw launched as Clawdbot in November 2025. It was renamed Moltbot on January 27, 2026 following trademark complaints from Anthropic, then renamed again to OpenClaw on January 30, 2026." } }, { "@type": "Question", "name": "What is the difference between OpenClaw and Claude Code?", "acceptedAnswer": { "@type": "Answer", "text": "Claude Code is a terminal-based coding assistant that resets context between sessions. OpenClaw is a persistent background agent with local long-term memory that runs continuously, accepts instructions from chat apps, and can operate any model including Claude, GPT, or DeepSeek." } } ] }
Run AI for FREE Forever — No GPU, No API Key
writing{variant="document" id="58321" title="SEO Description"}Want to run AI for FREE without buying a GPU, paying for a subscription, or using an API key? In this video, I'll show you how to run AI locally on your computer using a completely free setup. You'll learn how to run AI models without expensive cloud services, avoid monthly subscriptions, and use your own computer to process AI tasks. I'll also show you the setup process, recommended models, hardware requirements, and how to get started even if you don't have a dedicated GPU. Whether you want to run an AI chatbot, LLM, coding assistant, or other AI tools locally, this method can help you use AI without recurring costs. 🔥 What you'll learn:• How to run AI for free• How to run AI without a GPU• How to run AI locally• How to use AI without a subscription• How to run AI without an API key• Best free local AI models• CPU vs GPU AI performance• How to set up local AI If you're looking for a free AI alternative to expensive subscriptions, this tutorial is for you. #FreeAI #LocalAI #AI #NoGPU #ArtificialIntelligence writing{variant="document" id="58321" title="SEO Description"} Want to run AI for FREE without buying a GPU, paying for a subscription, or using an API key? In this video, I'll show you how to run AI locally on your computer using a completely free setup. You'll learn how to run AI models without expensive cloud services, avoid monthly subscriptions, and use your own computer to process AI tasks. I'll also show you the setup process, recommended models, hardware requirements, and how to get started even if you don't have a dedicated GPU. Whether you want to run an AI chatbot, LLM, coding assistant, or other AI tools locally, this method can help you use AI without recurring costs. 🔥 What you'll learn: • How to run AI for free • How to run AI without a GPU • How to run AI locally • How to use AI without a subscription • How to run AI without an API key • Best free local AI models • CPU vs GPU AI performance • How to set up local AI If you're looking for a free AI alternative to expensive subscriptions, this tutorial is for you. #FreeAI #LocalAI #AI #NoGPU #ArtificialIntelligence🔑
I Cancelled My $200 AI Coding Subscription for This Free Terminal Agent
I was paying $200 a month for AI coding tools. Then I switched to OpenCode — a free, open source AI coding agent that runs in your terminal — and I haven't gone back. I was paying $200 a month for AI coding tools. Then I switched to OpenCode — a free, open source AI coding agent that runs in your terminal — and I haven't gone back. In this video I break down exactly why I cancelled, what OpenCode does better than Claude Code and Cursor, where it still falls short, and how to set it up in under 10 minutes. OpenCode is MIT licensed, works with 75+ model providers including Claude, GPT, Gemini and local models via Ollama, and ships as a terminal UI, desktop app and IDE extension. If you're tired of vendor lock-in, per-seat pricing, or sending your codebase to someone else's cloud, this one's for you. ⏱️ CHAPTERS 00:00 The $200 problem 00:xx What OpenCode actually is 00:xx Install & first run 00:xx Bring your own model (Claude, GPT, Gemini, local) 00:xx OpenCode vs Claude Code — head to head 00:xx Running it fully offline 00:xx Where OpenCode still loses 00:xx Should you cancel too? 🔗 LINKS OpenCode: https://opencode.ai Docs: https://opencode.ai/docs GitHub: https://github.com/sst/opencode My config / dotfiles: [your link] 💬 Are you still paying for an AI coding subscription? Tell me what you're using in the comments. #opencode #aicoding #opensource
How to Run Any AI Model Offline in 5 Minutes (Ollama Tutorial)
Want to run powerful AI models like Llama 3, Mistral, or DeepSeek completely offline, no internet, no subscriptions, no data sent to the cloud? In this video, I'll show you how to set up Ollama and run any AI model locally on your computer in under 5 minutes, even if you've never touched the command line before. We'll cover installing Ollama on Windows, Mac, and Linux, downloading and running your first local AI model, chatting with it completely offline, and switching between different models depending on your hardware and use case. Whether you're a developer who wants full privacy, someone tired of paying for ChatGPT, or just curious about how local AI works, this tutorial will get you up and running fast. Timestamps 0:00 Intro – Why run AI offline? 0:45 What is Ollama? 1:30 Installing Ollama (Windows/Mac/Linux) 2:15 Downloading your first model 3:00 Running the model offline 4:00 Tips for choosing the right model for your PC 4:45 Final thoughts Links Mentioned Ollama official site: https://ollama.com Model library: https://ollama.com/library If this helped you, drop a like and subscribe for more AI tutorials, no fluff, just practical step-by-step guides. Follow me: Twitter/X: [your link] Instagram: [your link] Discord: [your link] #Ollama #LocalAI #AITutorial
Cursor + OmniRoute Setup Tutorial: Use FREE Open-Source AI Models in Cursor (2026 Guide)
Learn how to connect Cursor to OmniRoute, a free and open-source MIT-licensed AI gateway that routes your coding requests across 352+ providers — including 150+ free tiers worth roughly 1.51 billion free tokens per month — through a single OpenAI-compatible endpoint. In this 2026 tutorial, you'll install OmniRoute, run it locally on port 20128, and configure Cursor to use free models like Claude, GPT, Gemini, GLM, DeepSeek, Kimi K3, and MiniMax without hitting Cursor's paid credit limits. What you'll learn in this video: This tutorial walks through installing the OmniRoute npm package globally, launching the local API and dashboard on localhost:20128, and pointing Cursor's model settings at the OmniRoute endpoint so every AI request in Cursor is automatically routed to the best available free or low-cost model. You'll also see how OmniRoute's "auto" routing mode works, how the four-tier fallback system (Subscription → API Key → Cheap → Free) keeps you coding even when one provider's quota runs out, and how the built-in token compression engine can reduce eligible context by up to 89% so your free quota lasts longer. Timestamps: 00:00 Introduction — Why use OmniRoute with Cursor 00:00 What is OmniRoute (free open-source AI gateway explained) 00:00 Installing OmniRoute (npm install -g omniroute) 00:00 Running the OmniRoute dashboard on localhost:20128 00:00 Connecting Cursor to OmniRoute's OpenAI-compatible endpoint 00:00 Testing free models: Claude, GPT, Gemini, DeepSeek, GLM 00:00 Setting up Auto Combo routing and fallback tiers 00:00 Token compression and saving your free quota 00:00 Troubleshooting common connection issues 00:00 Final thoughts and next steps Frequently Asked Questions: Is OmniRoute really free? Yes — OmniRoute itself is free and open-source under the MIT license, and it catalogs over 150 free-tier provider entries so you can access AI models like Claude, GPT, Gemini, DeepSeek, and Kimi K3 without paying, though some premium providers behind OmniRoute may still require your own API key if you want to use paid tiers. Does OmniRoute work with Cursor specifically? Yes — OmniRoute exposes an OpenAI-compatible endpoint at localhost:20128/v1 that you can plug directly into Cursor's model configuration, alongside support for Claude Code, Codex CLI, Cline, GitHub Copilot, and other coding tools. Do I need an API key to start? No — OmniRoute works out of the box with zero configuration using its keyless "auto" model route, and you can add your own provider API keys later to unlock additional free tiers or paid models. Is my code or data sent to OmniRoute's servers? No — OmniRoute runs entirely locally on your machine with local-first, encrypted storage, so your prompts and credentials stay on your own computer. Resources mentioned in this video: OmniRoute GitHub repository: github.com/diegosouzapw/OmniRoute OmniRoute official site: omniroute.online Cursor: cursor.com If this tutorial helped you set up free AI models in Cursor, consider subscribing for more open-source AI tooling guides, and drop a comment if you hit any errors during setup — I'll help troubleshoot. #Cursor #OmniRoute #FreeAI #OpenSourceAI #AICodingTools #CursorAI #ClaudeAI #DeepSeek #AIforDevelopers #CodingTutorial2026
OmniRoute + OpenCode Setup 100% FREE Unlimited AI Coding (2026 Tutorial)
Learn how to set up OmniRoute inside OpenCode and unlock 100% free, unlimited AI coding — no credit card, no API key required to get started. In this step-by-step 2026 tutorial, I show you exactly how to install OmniRoute, connect it as a custom provider in OpenCode, and route your coding agent across 339+ AI providers (90+ with free tiers, 56 free forever) including Claude, GPT, Gemini, DeepSeek, Kimi, and GLM — all through a single OpenAI-compatible endpoint. OmniRoute is a free, open-source MIT-licensed AI gateway that sits between OpenCode and every major model provider. Instead of hitting rate limits or paying for expensive API keys, OmniRoute auto-fails over between providers in milliseconds, drains your free-tier quotas before touching paid ones, and even compresses tool output by up to 95% so your tokens go further. Once it's running locally on port 20128, you point OpenCode's provider config at it and every model on the OmniRoute catalog becomes available inside your terminal coding agent. What you'll learn in this video: how to install Node.js and npm if you don't already have them, how to install OpenCode and OmniRoute globally with a single npm command, how to start the OmniRoute server and open its local dashboard, how to connect free providers with zero configuration, how to edit your OpenCode config file (~/.config/opencode/opencode.json) to add OmniRoute as a custom provider using the @ai-sdk/openai-compatible adapter, and how to pick between model routes like auto, auto/coding, auto/fast, and auto/cheap depending on whether you want quality, speed, or cost savings. This setup works as a genuinely free alternative to paying for Claude Code, Cursor, GitHub Copilot, or standalone API keys from OpenAI, Anthropic, or Google — making it ideal for developers, students, and anyone experimenting with AI-assisted coding on a budget. Whether you searched for "omniroute opencode," "how to install omniroute," "omniroute setup," "free ai for coding," or "opencode alternative," this guide covers the full workflow from a blank terminal to a working AI coding agent. Timestamps: 0:00 Intro — why OmniRoute + OpenCode 0:00 Installing Node.js, npm, and OpenCode 0:00 Installing and starting OmniRoute 0:00 Connecting free AI providers (no credit card) 0:00 Editing the OpenCode config file 0:00 Choosing auto / auto-coding / auto-fast / auto-cheap models 0:00 Testing your free AI coding agent 0:00 Tips to avoid rate limits and maximize free tokens Links mentioned: OmniRoute: https://omniroute.online/ OmniRoute GitHub: https://github.com/diegosouzapw/OmniRoute OpenCode: https://opencode.ai/ If this helped you set up a completely free AI coding workflow, consider subscribing for more tutorials on OmniRoute, OpenCode, Claude Code, and other free AI developer tools. #OmniRoute #OpenCode #FreeAI #AICoding #ClaudeCode
Claude Desktop + OpenRouter Setup (Free Open Source Models)
Claude Desktop can run entirely on OpenRouter's free AI models — no Anthropic account, no subscription, no credit card. This is the complete 2026 setup using Gateway mode (third-party inference), plus the fix for the #1 problem: free models like Gemma 4 and Nemotron 3 not showing up in the model picker. ⚡ THE 60-SECOND VERSION 1. Get a free API key at openrouter.ai/keys (starts with sk-or-v1-) 2. Claude Desktop → Help → Troubleshooting → Enable Developer Mode 3. Developer → Configure Third-Party Inference 4. Inference provider: Gateway Gateway base URL: https://openrouter.ai/api Gateway API key: your sk-or-v1-... key Gateway auth scheme: bearer 5. Click "Apply locally" → FULLY quit Claude Desktop → reopen 6. Choose "Continue with Gateway" on the start screen 7. Add your free model IDs under Models (see 08:15 — this step is required) 🔧 WHY YOUR MODEL PICKER IS EMPTY Claude Desktop's auto-discovery only shows models whose IDs look like Claude models. Gemma, Nemotron and GPT-OSS get filtered out. You must list them explicitly in the Models section of the config window. Full walkthrough at 08:15. 💯 FREE OPENROUTER MODELS USED (August 2026) nvidia/nemotron-3-ultra-550b-a55b:free — 1M context, best all-round free model google/gemma-4-31b-it:free — 262K context, vision + tools openai/gpt-oss-20b:free — 131K context, fast and light poolside/laguna-s-2.1:free — 262K context, coding cohere/north-mini-code:free — 256K context, coding openrouter/free — auto-picks a free model for you 📊 FREE TIER LIMITS 20 requests per minute. Roughly 50 requests/day on a zero-balance account, rising to about 1,000/day once you've purchased $10 in credits at any point (credits don't expire). Verify current numbers at openrouter.ai/docs — these change. ⚠️ HONEST DISCLAIMER This gives you Claude Desktop's INTERFACE for free — not Claude Opus or Sonnet for free. Routing actual Claude models through OpenRouter costs normal API rates. Free models are capable but they are not Claude-tier. 🕐 CHAPTERS 00:00 What this actually gets you (and what it doesn't) 01:10 Why route Claude Desktop through OpenRouter 02:05 Creating your free OpenRouter API key 03:20 Enabling Developer Mode in Claude Desktop 04:15 Configure Third-Party Inference: the exact 4 fields 05:40 Apply locally + the full restart people skip 🔗 LINKS OpenRouter keys: https://openrouter.ai/keys Official Claude Desktop integration guide: https://openrouter.ai/docs/cookbook/coding-agents/claude-desktop-integration Anthropic gateway docs: https://claude.com/docs/third-party/claude-desktop/gateway Free models list: https://openrouter.ai/collections/free-models Written guide with copy-paste config: [your blog URL] #ClaudeDesktop #OpenRouter #FreeAI #AITools #claudeai Claude Desktop for FREE with OpenRouter (2026) — Full Setup + The Model Picker Fix
Codex + OmniRoute Setup = FREE Unlimited AI Tokens (Setup in 7 Minutes)
Stop burning credits in Codex CLI. In this video I connect OpenAI Codex to OmniRoute — a free, open-source, MIT-licensed local AI gateway that pools 290+ providers and 90+ free tiers behind one endpoint — and get it running end to end in about 7 minutes. OmniRoute runs on your own machine (localhost:20128), auto-falls back when a provider hits its quota, and stacks RTK + Caveman compression to cut token usage dramatically. Point Codex at one base URL and you get Claude, GPT, Gemini, Kimi, GLM, DeepSeek and hundreds more through a single config. ⚠️ Honest disclaimer: "unlimited" is shorthand for pooled free tiers (~1.4–1.5B tokens/month by OmniRoute's own pool-deduped count), not infinite tokens. Some providers restrict gateway use in their terms — check each provider's ToS before you route production work through it. This is an educational walkthrough of an open-source tool, not a way to bypass anyone's billing. ⏱️ CHAPTERS 00:00 — Why Codex eats your credits 00:45 — What OmniRoute actually is (290 providers, one endpoint) 01:30 — Install: npm i -g omniroute 02:20 — First run + the dashboard tour 03:10 — Connecting your first FREE providers 04:15 — Pointing Codex CLI at OmniRoute (config.toml) 05:20 — Testing it: model "auto" and auto-fallback in action 06:10 — Combos, routing strategies & token compression 06:50 — Costs, limits and what to watch out for 🔗 LINKS OmniRoute (GitHub): https://github.com/diegosouzapw/OmniRoute OmniRoute site: https://omniroute.online OpenAI Codex CLI: https://github.com/openai/codex 💬 Which provider combo are you running? Drop it in the comments — I'm collecting the best free-tier stacks for a follow-up video. 👍 Like + subscribe for more AI coding workflow videos. #Codex #OmniRoute #AICoding #OpenSource #developertools omniroute setup omniroute codex how to install omniroute codex omniroute codex unlimited omniroute how to setup omniroute install omniroute omniroute installation omniroute free unlimited codex omniroute install omniroute github setup omniroute omni route codex omniroute tutorial how to use omniroute how to use codex unlimited codex free unlimited omniroute combo omniroute combos omniroute + codex codex free codex codex with omniroute how to download omniroute how to use codex free onmiroute free ai how omniroute works omni route what is omniroute omniroute vs code codex token codex router use codex for free free codex omniroute config ominiroute como usar omniroute how to set up omniroute omni router
Claude Code + MiniMax M3: The 5-Line Config Nobody Explains
Claude Code doesn't care which model is behind the endpoint. In this video I point it at MiniMax M3 and cut my coding costs by ~90% — full config, verification steps, and the errors everyone hits on the first try. MiniMax M3 shipped June 1, 2026 and scores around 59% on SWE-Bench Pro with a 1M token context window, at roughly $0.23/M input and $0.96/M output tokens. I also cover OpenCode, which has built-in MiniMax-M3 support with zero config files. ⏱️ CHAPTERS 00:00 The $200/month problem 00:xx What MiniMax M3 actually scores 00:xx Getting your MiniMax API key 00:xx Method 1: ~/.claude/settings.json 00:xx The base URL trap (international vs China) 00:xx Why you MUST set the auto-compact window to 1,000,000 00:xx Method 2: environment variables (these override settings.json) 00:xx Method 3: OpenCode — zero config needed 00:xx Verifying with /status and /model 00:xx Anthropic-compatible vs OpenAI-compatible endpoints 00:xx Troubleshooting: auth errors, wrong region, context overflow 00:xx Where Claude still wins (honest limits) 00:xx Cost breakdown after 30 days 🔧 THE CONFIG (also in the pinned comment) File: ~/.claude/settings.json Base URL (international): https://api.minimax.io/anthropic Base URL (China): https://api.minimaxi.com/anthropic Model ID: MiniMax-M3 Set CLAUDE_CODE_AUTO_COMPACT_WINDOW to 1000000 🔗 LINKS MiniMax docs — https://platform.minimax.io/docs/token-plan/claude-code Other tools (Zed, Kilo, Droid, Xcode) — https://platform.minimax.io/docs/token-plan/other-tools OpenCode — https://opencode.ai/docs/models/ Claude Code setup — https://code.claude.com/docs/en/setup Pricing and tier names change often — check the platform before you subscribe. Verified as of the upload date. #claudecode #minimax #opencode claude code minimax setup, minimax m3 claude code, opencode minimax, anthropic base url minimax, claude code alternative model, claude code custom api, minimax coding plan, claude code cheaper, ai coding agent terminal, swe-bench pro
omniroute setup in claude desktop
OmniRoute is a free, open-source (MIT) local AI gateway that routes Claude Desktop, Claude Code, Cursor, Cline and other OpenAI-compatible tools to 200+ AI providers through a single endpoint at http://localhost:20128/v1. In this full tutorial I install it with npm, connect it to Claude Desktop as an MCP server, add free-tier provider keys, and set up auto-fallback so requests keep working when one provider hits its rate limit. Note: OmniRoute does not unlock paid Claude plans. It pools the documented free tiers that providers already offer, plus any API keys or subscriptions you already own. Free tiers have rate limits and providers change them often — check each provider's terms before relying on it. ⏱️ Timestamps 00:00 What OmniRoute actually is (and what it isn't) 00:00 Requirements: Node.js, npm, Claude Desktop 00:00 Install OmniRoute (npm i -g omniroute) 00:00 First request with zero config using the "auto" model 00:00 Connecting OmniRoute to Claude Desktop via MCP 00:00 Adding free provider keys in the dashboard 00:00 Routing strategies and auto-fallback explained 00:00 Token compression and cost savings 00:00 Troubleshooting common setup errors 00:00 Is it worth it? Honest verdict 🔗 Resources OmniRoute GitHub: https://github.com/diegosouzapw/OmniRoute OmniRoute site: https://omniroute.online/ Claude Desktop: https://claude.ai/download MCP docs: https://modelcontextprotocol.io ❓ Questions answered in this video What is OmniRoute and how does it work? How do I connect OmniRoute to Claude Desktop? Is OmniRoute free, and what are the limits? How does auto-fallback between AI providers work? OmniRoute vs OpenRouter vs LiteLLM — what's the difference? Can I self-host OmniRoute with Docker? 💬 Which provider combo are you running? Drop your setup in the comments. related keywords: omniroute setup omniroute claude omniroute omni route claude how to connect omniroute to claude omniroute claude code omniroute claude setup omni router setup omniroute claude desktop omni route claude omniroute how to setup omniroute how to install omniroute in claude how to install omniroute how to use omniroute omni route claude code omnirouter omniroute setup windows omniroute github omniroute claude code setup claude desktop free how to install omni route omniroute setup claude omniroute with claude ominiroute how to setup omni route github omniroute omni route tutorial omni route setup claude code omniroute omniroute codex claude omni route how to set up omniroute omniroute + claude nick ayala how to use omni route* how to download omniroute omni route with claude code how to use omniroute with claude claude desktop install omniroute omni route installation claude code + omniroute omniroute tutorial omni route opencode setup omniroute #OmniRoute #ClaudeDesktop #OpenSourceAI
Install & Setup Ollama Cloud on Windows 10/11 — Run Huge AI Models With No GPU
Learn how to install and set up Ollama Cloud AI models on Windows 10 and Windows 11 — step by step, no GPU required. In this full 2026 tutorial I show you how to download the Ollama Windows installer, create a free ollama.com account, sign in from the terminal with ollama signin, pull your first cloud model, and run large open models like Gemma 4, Qwen 3.5, DeepSeek V4 Flash, GLM 5.2, Kimi K3 and gpt-oss straight from your PC while the heavy compute runs in Ollama's cloud. Ollama Cloud lets you keep using the same local Ollama commands, tools and apps you already know, but offloads models that would never fit on a normal laptop. You'll also learn how to create an OLLAMA_API_KEY for direct API access, connect Ollama Cloud to Python and JavaScript, understand the Free / Pro / Max usage limits, check your usage, and switch back to local-only mode if you want everything offline. ⏱️ TIMESTAMPS 00:00 – What is Ollama Cloud (and why it matters on Windows) 01:05 – Ollama Cloud vs local models: what changes 02:10 – System requirements for Windows 10 / 11 03:00 – Downloading & installing OllamaSetup.exe (no admin rights needed) 05:20 – Creating your free ollama.com account 06:30 – Signing in with ollama signin 08:00 – Finding cloud models in the library (the cloud tag) 09:40 – Pulling and running your first cloud model 12:00 – Using the Ollama desktop app instead of the terminal 14:15 – Creating an API key & setting OLLAMA_API_KEY on Windows 17:00 – Calling Ollama Cloud from Python and JavaScript 20:10 – Free vs Pro vs Max: usage limits and concurrency 22:30 – Checking your usage and avoiding limit errors 24:00 – Switching to local-only mode (privacy) 25:30 – Troubleshooting common errors 27:00 – Final thoughts + what to watch next 🔗 LINKS Download Ollama: https://ollama.com/download Cloud models list: https://ollama.com/search?c=cloud Ollama Cloud docs: https://docs.ollama.com/cloud API keys: https://ollama.com/settings/keys Pricing & limits: https://ollama.com/pricing 💬 Which cloud model should I test next — Kimi K3 or DeepSeek V4 Pro? Tell me in the comments. 👍 If this helped, like and subscribe for more local AI and open-model tutorials. Note: Ollama retires older cloud models periodically, so check the docs page above for the current model list if a name in this video no longer works. #Ollama #OllamaCloud #LocalLLM #Windows11 #AITutorial