Can NVIDIA H100 80GB run DeepSeek R1 70B?
70B parameter LLM model on 80GB HBM3
VRAM Requirements
DeepSeek R1 70B is a 70B parameter model. At full precision (FP16), it requires 140GB of VRAM. Your NVIDIA H100 80GB has 80GB, so you'll need to quantize it to 8-bit (Q8) to fit.
Maximum quality, no quantization
Near-lossless, ~50% size reduction
Good quality, ~75% size reduction
Recommended system RAM: 160GB DDR5 (2x GPU VRAM minimum for model overflow)
What This Means in Practice
Running DeepSeek R1 70B at 8-bit quantization on NVIDIA H100 80GB gives you virtually identical quality to full precision while using roughly half the VRAM. Most users cannot distinguish Q8 output from FP16. This is the recommended precision for daily use — it's the best balance of quality and resource usage.
How to Set It Up
Step 1: Install Ollama
curl -fsSL https://ollama.com/install.sh | shOllama is the easiest way to run local LLMs. Works on Linux, macOS, and Windows.
Step 2: Download and run DeepSeek R1 70B
ollama run deepseek-r1:70bThis downloads the model (~70GB). First run takes a few minutes.
Step 3: Verify GPU is being used
nvidia-smiCheck that VRAM usage increases when the model loads. You should see ~70GB used.
NVIDIA H100 80GB Specs
Other GPUs That Run DeepSeek R1 70B
Other LLM Models on NVIDIA H100 80GB
About DeepSeek R1 70B
Strong reasoning model. Same tier as Llama 70B for hardware requirements.