DeepSeek R1 Distill 32B (Ollama)

The 32B R1 distill in 4-bit via Ollama — near-frontier reasoning on a single GPU.

Overview

Served through Ollama's 4-bit build (~20 GB). Use the Ollama API from your code, or switch the deployment to the Open WebUI template for a chat interface.

Key features

• ✓
  Strong step-by-step reasoning
• ✓
  Simple Ollama API
• ✓
  MIT licence

Use cases

• →
  Hard maths / coding questions
• →
  Research on reasoning
• →
  Batch evaluation

On this template

Runs on the Ollama template, exposing its Ollama API at a private HTTPS address. You also get root SSH and JupyterLab.

OLLAMA_PULL

deepseek-r1:32b

Quick start

1. Click Deploy and pick an available GPU — only offers with enough VRAM are shown.
2. Wait for the status to turn running. The first start downloads the model, which can take a few minutes.
3. Use the connection details on your rental page:

curl -u edge:<app-token> https://r12-abcd1234-app.gpu.clearlayer.ca/api/generate \
  -d '{"model": "deepseek-r1:32b", "prompt": "Hello!", "stream": false}'

import requests

r = requests.post("https://r12-abcd1234-app.gpu.clearlayer.ca/api/chat", auth=("edge", "<app-token>"), json={
    "model": "deepseek-r1:32b", "stream": False,
    "messages": [{"role": "user", "content": "Hello!"}],
})
print(r.json()["message"]["content"])