Can I run nomic-embed-text?

nomic-embed-text system requirements

Memory needed at 4K context, counting model weights, KV cache, compute buffers and runtime overhead. Download sizes come from the official Ollama registry.

Figures marked (est.) approximate the KV cache because this model's architecture details are not published. They are indicative rather than exact.

How to run nomic-embed-text locally

1. 1.Install Ollama for Windows, macOS or Linux.
2. 2.Run this in a terminal:ollama run nomic-embed-text:137m-v1.5-fp16
3. 3.The weights download on first run, then an interactive prompt opens.

Frequently asked questions about nomic-embed-text

How much VRAM do I need to run nomic-embed-text?

At 4K context, the smallest published build of nomic-embed-text (F16) needs roughly 0.9 GB of GPU memory once weights, KV cache, compute buffers and runtime overhead are counted. Bigger quantizations and longer context windows need more. It can also run partly or entirely on the CPU using system RAM, more slowly.

Can I run nomic-embed-text without a dedicated GPU?

Yes, but slowly. Without a GPU the model runs on the CPU using system RAM, which usually means a few tokens per second rather than dozens. You would need at least 0.9 GB of free RAM for the smallest build.

How big is the nomic-embed-text download?

The smallest published build is 0.3 GB. Leave some extra free disk space beyond the download itself.

How do I run nomic-embed-text locally?

Install Ollama, then run "ollama run nomic-embed-text:137m-v1.5-fp16" in a terminal. The weights download on first use and an interactive session opens.