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🚀 Free Claude Code Setup with Ollama

Use Anthropic's Claude Code agentic workflow — completely free — powered by open-source models via Ollama. No Anthropic subscription. No API key. No paid plan. Just your terminal.

Architecture Diagram


📖 Table of Contents


What Is This?

Claude Code is Anthropic's open-source agentic coding tool. It lives in your terminal and can:

  • 📂 Read your entire codebase
  • ✍️ Write and edit files directly
  • ▶️ Run your code and fix errors automatically
  • 🧠 Plan and execute multi-step coding tasks
  • 🌐 Search the web for documentation

By default it talks to Anthropic's paid Claude models. But here's the trick:

Ollama built their API to speak the exact same language as Anthropic's API. So you can redirect Claude Code → Ollama → completely free open-source models, and Claude Code has no idea it's not talking to Anthropic anymore.

YOU → Claude Code CLI → Ollama → Free Models (cloud or local)
                                 ↙              ↘
                          Cloud Models      Local Models
                      (Ollama's servers)  (Your machine)
                        Free w/ limits     Free forever

How It Works

Claude Code is just a CLI tool that sends requests to any server that speaks the Anthropic Messages API format.

Ollama v0.14.0+ added full compatibility with the Anthropic Messages API. This means:

  1. You install Claude Code (the free open-source CLI by Anthropic)
  2. You install Ollama (the free model runner)
  3. You point Claude Code at Ollama instead of Anthropic's servers
  4. Claude Code works exactly the same — but powered by free open-source models

Three environment variables are all it takes:

ANTHROPIC_AUTH_TOKEN=ollama   # dummy value, Ollama doesn't need real auth
ANTHROPIC_API_KEY=""          # empty, no real key needed
ANTHROPIC_BASE_URL=http://localhost:11434  # points to your local Ollama

Prerequisites

Requirement Version Check
Node.js v18 or higher node --version
Ollama v0.14.0 or higher ollama --version
OS Windows 10/11, macOS 11+, Linux
RAM (cloud models) 4 GB minimum
RAM (local models) 8–16 GB recommended

Installation

Step 1 — Install Node.js

Download from nodejs.org and install. Then verify:

node --version   # should show v18+

Step 2 — Install Ollama

Linux:

curl -fsSL https://ollama.com/install.sh | sh

macOS:

brew install ollama

Windows — Download the installer from ollama.com/download/windows and run it. No admin rights needed.

Verify:

ollama --version

Windows users with a small C: drive: Redirect model storage to another drive before downloading any models:

[System.Environment]::SetEnvironmentVariable("OLLAMA_MODELS", "D:\ollama\models", "User")

Then restart PowerShell.

Step 3 — Install Claude Code

npm install -g @anthropic-ai/claude-code

Verify:

claude --version

Cloud Models (Free, No Download)

Cloud models run on Ollama's servers — nothing downloads to your machine. This is the easiest way to get started.

⚠️ Note: Ollama cloud models have a free usage tier. Heavy usage may require an Ollama account. For unlimited free usage, use local models instead.

Launch with the easiest command

ollama launch claude --model glm-5:cloud

That's it. One command. Claude Code opens with a free cloud model.

All available cloud models

Model Command Best For
GLM-5 ollama launch claude --model glm-5:cloud Long codebases, complex tasks
MiniMax M2.7 ollama launch claude --model minimax-m2.7:cloud Real-world engineering (top ranked)
Kimi K2.5 ollama launch claude --model kimi-k2.5:cloud Multi-file agentic projects
Qwen3.5 ollama launch claude --model qwen3.5:cloud Code generation, huge context (1M tokens)
DeepSeek V3.2 ollama launch claude --model deepseek-v3.2:cloud Math-heavy projects
Gemma 4 ollama launch claude --model gemma4:cloud Vision + coding (can read images)
Devstral Small 2 ollama launch claude --model devstral-small-2:cloud Fast, European privacy
Nemotron 3 Super ollama launch claude --model nemotron-3-super:cloud Multi-agent reasoning

Browse all cloud models at ollama.com/search?c=cloud


Local Models (100% Offline, Free Forever)

Local models run entirely on your machine. No internet needed after download. No usage limits. No data leaves your computer.

Step 1 — Pull a model

Choose based on your available RAM:

Model Command Download Size Min RAM Quality
qwen2.5-coder:0.5b ollama pull qwen2.5-coder:0.5b 398 MB 4 GB Basic
qwen2.5-coder:1.5b ollama pull qwen2.5-coder:1.5b 986 MB 4 GB Light
qwen2.5-coder:3b ollama pull qwen2.5-coder:3b 1.9 GB 8 GB Good
qwen2.5-coder:7b ollama pull qwen2.5-coder:7b 4.7 GB 16 GB Recommended
qwen2.5-coder:14b ollama pull qwen2.5-coder:14b 9 GB 20 GB Strong
qwen3:8b ollama pull qwen3:8b 5.2 GB 16 GB Reasoning

Models are saved to:

  • Linux / macOS: ~/.ollama/models/
  • Windows: C:\Users\<you>\.ollama\models\

To change where models save (e.g. to a bigger drive):

# Linux / macOS
export OLLAMA_MODELS=/path/to/big/drive

# Windows PowerShell (permanent)
[System.Environment]::SetEnvironmentVariable("OLLAMA_MODELS", "D:\ollama\models", "User")

Step 2 — Launch Claude Code with local model

ollama launch claude --model qwen2.5-coder:7b

Manage your local models

ollama list              # see all downloaded models
ollama rm modelname      # delete a model to free space
ollama pull modelname    # download a model
ollama show modelname    # see model info and size

How to Switch Models

Switching models is just changing one word in the launch command. You can switch between cloud and local freely.

Quick switch examples

# Using GLM-5 cloud (what most people start with)
ollama launch claude --model glm-5:cloud

# Switch to Kimi K2.5 for a multi-file project
ollama launch claude --model kimi-k2.5:cloud

# Switch to a local model for privacy / offline work
ollama launch claude --model qwen2.5-coder:7b

# Switch to Qwen3.5 for massive context (1M tokens)
ollama launch claude --model qwen3.5:cloud

# Switch to Gemma 4 to analyze an image in your project
ollama launch claude --model gemma4:cloud

Make a shortcut (so you don't retype every time)

Linux / macOS — add to your ~/.bashrc or ~/.zshrc:

alias cc='ollama launch claude --model glm-5:cloud'
alias cc-kimi='ollama launch claude --model kimi-k2.5:cloud'
alias cc-local='ollama launch claude --model qwen2.5-coder:7b'

Reload: source ~/.bashrc

Windows PowerShell — run notepad $PROFILE and add:

function cc { ollama launch claude --model glm-5:cloud }
function cc-kimi { ollama launch claude --model kimi-k2.5:cloud }
function cc-local { ollama launch claude --model qwen2.5-coder:7b }

Restart PowerShell. Now just type cc to launch.

Always navigate to your project first

cd /path/to/your/project
ollama launch claude --model glm-5:cloud

Then run /init inside Claude Code so it scans your project.


Free Alternatives via OpenRouter

OpenRouter is another way to access free models. It acts as a router between Claude Code and many different AI providers, some of which are free.

Setup with OpenRouter

  1. Create a free account at openrouter.ai
  2. Get your API key from the dashboard
  3. Configure Claude Code:
# Linux / macOS
export ANTHROPIC_API_KEY="your-openrouter-key"
export ANTHROPIC_BASE_URL="https://openrouter.ai/api/v1"
export ANTHROPIC_AUTH_TOKEN="your-openrouter-key"

# Then launch claude directly
claude --model openrouter/google/gemma-3-27b-it:free

Windows PowerShell:

$env:ANTHROPIC_API_KEY = "your-openrouter-key"
$env:ANTHROPIC_BASE_URL = "https://openrouter.ai/api/v1"
claude --model openrouter/google/gemma-3-27b-it:free

Free models on OpenRouter (as of April 2026)

Model OpenRouter ID
Gemma 3 27B google/gemma-3-27b-it:free
Llama 3.3 70B meta-llama/llama-3.3-70b-instruct:free
DeepSeek V3 deepseek/deepseek-chat:free
Mistral 7B mistralai/mistral-7b-instruct:free
Qwen3 30B qwen/qwen3-30b-a3b:free

Check openrouter.ai/models?q=free for the latest free models list. It updates frequently.

Ollama vs OpenRouter — which to use?

Ollama Cloud OpenRouter Free
Setup Easiest (one command) Needs account + API key
Models Ollama's curated list 100+ models from everywhere
Free tier Yes, with limits Yes, rate limited
Local models ✅ Yes ❌ No
Privacy Good Varies by provider
Best for Getting started fast Accessing more model variety

Model Comparison Table

All models below are free and open-source. Benchmarks from SWE-bench Verified (real GitHub issues) and LiveCodeBench (algorithmic coding) as of April 2026.

Model Made By SWE-bench LiveCode Context Special Strength Cloud Command
MiniMax M2.7 🏆 MiniMax 🇨🇳 80.2% 1M Top real-engineering score minimax-m2.7:cloud
Gemma 4 🆕 Google 🇺🇸 80.0% 256K Vision + audio + code gemma4:cloud
GLM-5 Zhipu AI 🇨🇳 77.8% 200K Long codebase generation glm-5:cloud
Kimi K2.5 Moonshot 🇨🇳 76.8% 85% 256K 100 parallel sub-agents kimi-k2.5:cloud
Qwen3.5 Alibaba 🇨🇳 76.4% 83.6% 1M Biggest context, tool use qwen3.5:cloud
DeepSeek V3.2 DeepSeek 🇨🇳 74.4% 86.4% 128K Math + reasoning deepseek-v3.2:cloud
Devstral Small 2 Mistral 🇫🇷 128K Fast, EU privacy devstral-small-2:cloud
Nemotron 3 Super NVIDIA 🇺🇸 1M Multi-agent tasks nemotron-3-super:cloud

How to read benchmarks

  • SWE-bench Verified — model is given real GitHub bug reports and must fix them. Closest to actual dev work.
  • LiveCodeBench — algorithmic coding problems. Great for competitive-style tasks.
  • Higher % = better. Claude Opus 4.6 (paid) scores 80.8% on SWE-bench for reference.

Claude Code Tips & Commands

Once inside Claude Code (after launching), these are the most useful things to know:

First thing to do in any project

/init

This scans your project folder and creates a CLAUDE.md file with context about your codebase. Always run this first.

Useful slash commands

Command What it does
/init Scan project, set up Claude Code
/help Show all available commands
/clear Clear conversation history
/compact Compress context to save tokens
/model Show current model
/exit Exit Claude Code

Scheduled / automated tasks with /loop

# Check your PRs every 30 minutes
/loop 30m Check my open PRs and summarize their status

# Research news every hour
/loop 1h Find the latest AI news and summarize it

# Check for bugs every 15 minutes
/loop 15m Check for new GitHub issues and triage by priority

Non-interactive / headless mode (for scripts and CI/CD)

ollama launch claude --model kimi-k2.5:cloud --yes -- -p "explain how this codebase works"

The --yes flag skips all prompts. Everything after -- goes directly to Claude Code.

Web search (built in via Ollama)

Claude Code can search the web automatically when it needs current information. No extra setup needed when using Ollama.


FAQ

Q: Is this legal / against Anthropic's terms? A: Yes, completely fine. Claude Code is open-source software released by Anthropic. Anthropic built it to work with any Anthropic-compatible API. Ollama built that compatibility. You are using both tools exactly as designed.

Q: Why not just type claude instead of ollama launch claude? A: The claude command connects directly to Anthropic's paid servers and asks you to log in. ollama launch claude is Ollama launching the same CLI but routing it through free models. They look the same on screen but go to completely different backends.

Q: Will I lose anything vs the paid version? A: You lose access to Anthropic's Claude models (Opus, Sonnet, Haiku). Everything else — the agentic workflow, file reading, code execution, multi-step planning — works exactly the same. The free open-source models are within 5-10% of Claude Opus on most coding benchmarks.

Q: How do I know which model to pick? A: Start with glm-5:cloud (it's what most people default to). If you're working on large multi-file projects, try kimi-k2.5:cloud. If you need to pass images or designs to Claude Code, use gemma4:cloud. For maximum context (huge codebases), use qwen3.5:cloud.

Q: Are cloud models private? A: When using Ollama cloud models, your prompts are processed on Ollama's servers. For private/proprietary code, use local models instead — nothing leaves your machine.

Q: My C: drive is almost full. Where do models save? A: By default on Windows: C:\Users\<you>\.ollama\models\. Change it before pulling any models:

[System.Environment]::SetEnvironmentVariable("OLLAMA_MODELS", "D:\ollama\models", "User")

Q: The model is slow on my laptop. What should I do? A: Use a cloud model (glm-5:cloud) instead of a local model. Cloud models run on Ollama's servers so your hardware doesn't matter. Local models are only fast if you have a powerful NVIDIA or Apple Silicon GPU.

Q: Can I use this in VS Code? A: Yes. Install the Claude Code VS Code extension and add to your settings.json:

"claudeCode.environmentVariables": [
  { "name": "ANTHROPIC_API_KEY", "value": "not-needed" },
  { "name": "ANTHROPIC_BASE_URL", "value": "http://localhost:11434" },
  { "name": "ANTHROPIC_MODEL", "value": "qwen2.5-coder:7b" },
  { "name": "CLAUDE_CODE_DISABLE_NONESSENTIAL_TRAFFIC", "value": "1" }
]

Resources


Contributing

Found a better model? New free provider? Updated benchmark? PRs welcome.

Keep it simple. One doc. No fluff.


Last updated: April 2026 | Models and benchmarks change fast — check the links above for the latest.

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Step-by-step guide to running Claude Code for free using Ollama, open-source models, and OpenRouter.

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