DEV Community

Alex Spinov
Alex Spinov

Posted on

Ollama Has a Free Local LLM Runtime — Run Llama 3, Mistral, and Gemma on Your Machine

#ai #llm #ollama #free

OpenAI charges per token. Anthropic charges per token. Google charges per token. For development and testing, these costs add up fast — especially when you're iterating on prompts.

Ollama lets you run the same quality models locally. Llama 3 70B, Mistral, Gemma, CodeLlama — all running on your hardware. Zero API costs. Complete privacy.

What You Get Free

MIT licensed. Runs on macOS, Linux, Windows:

  • One-command install — curl -fsSL https://ollama.com/install.sh | sh
  • 50+ models — Llama 3, Mistral, Gemma, CodeLlama, Phi, Qwen, and more
  • OpenAI-compatible API — drop-in replacement for OpenAI SDK
  • GPU acceleration — NVIDIA, AMD, Apple Silicon
  • Model customization — Modelfiles for fine-tuned behavior
  • Multimodal — vision models (LLaVA) for image understanding
  • Embeddings — generate embeddings for RAG locally
  • Context window — up to 128K tokens on supported models
  • Concurrent requests — serve multiple users
  • REST API — localhost:11434 ready for any client

Quick Start 

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

# Run a model (downloads automatically)
ollama run llama3.2

# Or via API
curl http://localhost:11434/api/generate -d '{
  "model": "llama3.2",
  "prompt": "Explain Docker in one paragraph"
}'
Enter fullscreen mode Exit fullscreen mode

OpenAI SDK Compatibility 

from openai import OpenAI

# Just change the base URL — everything else stays the same
client = OpenAI(base_url="http://localhost:11434/v1", api_key="ollama")

response = client.chat.completions.create(
    model="llama3.2",
    messages=[{"role": "user", "content": "Write a Python function to merge two sorted lists"}]
)
print(response.choices[0].message.content)
Enter fullscreen mode Exit fullscreen mode

Your existing OpenAI code works with one line change.

What You Can Build

1. Local coding assistant — CodeLlama for code generation, review, debugging. Zero API cost.
2. RAG pipeline — embed documents locally, query with LLM. Complete privacy.
3. Chatbot development — iterate on prompts without paying per request.
4. Content generation — drafts, summaries, translations. Run overnight batch jobs free.
5. AI-powered CLI tools — pipe terminal output through LLMs for analysis.

Hardware Requirements

7B models (Llama 3.2, Mistral 7B): 8GB RAM, any modern CPU. Runs on M1 Mac.
13B models: 16GB RAM. Noticeable quality improvement over 7B.
70B models (Llama 3 70B): 48GB RAM or GPU with 40GB VRAM. Approaches GPT-4 quality.

Need AI integration help? Email spinov001@gmail.com

More free tiers: 65+ Free APIs Every Developer Should Bookmark

Top comments (0)