How to use Ollama with VS Code
Ollama with VS Code by installing the Ollama CLI and optionally the Ollama VS Code extension to run local AI models directly within your editor. You can invoke models via the terminal or through extension commands for chat and code generation.VERDICT
Ollama for local AI model hosting and fast offline inference within VS Code; it excels at privacy and low-latency local development compared to cloud-only APIs.| Tool | Key strength | Pricing | API access | Best for |
|---|---|---|---|---|
| Ollama | Local AI model hosting with VS Code integration | Free and open-source | Local CLI and VS Code extension | Offline AI development and chat |
| OpenAI API | Cloud-based powerful models with broad ecosystem | Freemium, pay per usage | REST API and SDKs | Scalable cloud AI applications |
| Anthropic Claude | High-quality conversational AI | Freemium, pay per usage | REST API and SDKs | Conversational AI and coding assistance |
| Google Gemini | Multimodal AI with Google ecosystem | Check pricing at Google Cloud | Cloud API | Multimodal AI and enterprise apps |
Key differences
Ollama runs AI models locally on your machine, providing privacy and low latency, while VS Code integration allows seamless AI-assisted coding and chat inside the editor. Unlike cloud APIs like OpenAI or Anthropic, Ollama does not require internet access once models are installed. The VS Code extension offers a user-friendly interface to interact with models without leaving the editor.
Side-by-side example: Using Ollama CLI in VS Code terminal
Run a local AI model from the VS Code integrated terminal using the Ollama CLI:
import os
import subprocess
# Example: Run Ollama chat model from Python subprocess
command = ["ollama", "chat", "llama2", "--prompt", "Write a Python function to reverse a string."]
result = subprocess.run(command, capture_output=True, text=True)
print(result.stdout)def reverse_string(s):
return s[::-1] VS Code extension usage example
After installing the Ollama VS Code extension, you can open the command palette (Ctrl+Shift+P) and select Ollama: Chat to start a chat session with a local model. You can also highlight code and invoke Ollama commands to get completions or explanations inline.
When to use each
Use Ollama with VS Code when you need offline AI model access, data privacy, or low-latency responses directly in your editor. Choose cloud APIs like OpenAI or Anthropic when you require the latest large models, scalability, or integrated cloud services.
| Scenario | Use Ollama | Use Cloud API |
|---|---|---|
| Offline development | ✔️ | ❌ |
| Data privacy | ✔️ | Depends on provider |
| Access to latest large models | Limited | ✔️ |
| Scalable cloud deployment | No | ✔️ |
| VS Code integration | Native extension | Via API calls |
Pricing and access
| Option | Free | Paid | API access |
|---|---|---|---|
| Ollama | Yes, fully free and open-source | No paid plans | Local CLI and VS Code extension |
| OpenAI API | Yes, limited free credits | Pay per usage | REST API and SDKs |
| Anthropic Claude | Yes, limited free credits | Pay per usage | REST API and SDKs |
| Google Gemini | Check Google Cloud pricing | Pay per usage | Cloud API |
Key Takeaways
- Use
Ollamafor local AI model hosting with VS Code for offline, private AI development. - The Ollama VS Code extension enables seamless chat and code generation inside the editor without cloud calls.
- Cloud APIs like
OpenAIandAnthropicoffer scalable, up-to-date models but require internet access. - Invoke Ollama models via CLI in VS Code terminal or use the extension commands for interactive workflows.
- Pricing for Ollama is fully free and open-source, ideal for developers prioritizing cost and privacy.