Step-by-step guide to running quantized reasoning models on your local Mac Studio or RTX GPU with zero cloud data transmission.
Running high-performance reasoning models locally ensures 100% data privacy, zero API rate limits, and offline availability.
| Model Size | Quantization | Minimum RAM / VRAM | Recommended Hardware |
|---|---|---|---|
| 8B / 7B | Q4_K_M | 8 GB | Apple M1/M2/M3 (16GB RAM) or RTX 3060 |
| 14B / 32B | Q4_K_M | 24 GB | Apple M-series (36GB+ RAM) or RTX 4090 |
| 70B | Q4_K_M | 48 GB | Mac Studio M2 Ultra (64GB+) or 2x RTX 3090 |
# 1. Install Ollama via Homebrew
brew install ollama
# 2. Start the local server
ollama serve
# 3. Pull and run DeepSeek R1 distilled model
ollama run deepseek-r1:14bYou can integrate your local Ollama server directly into Cursor, Continue.dev, or deploy Open-WebUI using Docker for a self-hosted ChatGPT interface.
Coding & Dev
Anthropic's top-tier reasoning model with exceptional coding ability, nuance, and 200k token context.
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