by Nomic AI
Nomic Embed Text.
embedding
open weights
edge
0B params
8K ctx
Smallest GPU
1× Nvidia GeForce GTX 1650 Super
Open embedding model — 69M Ollama pulls, the local default.
Smallest GPU to run it
See all quantisations →
1× Nvidia GeForce GTX 1650 Super.
Most-aggressive quantisation we have a working recommendation for. Lower precision = less VRAM = cheaper hardware, at a small accuracy cost.
FAQ
Frequently asked.
How do I run Nomic Embed Text?
Nomic Embed Text is open-weight, so you can self-host on rented GPUs. See the Run It Yourself tab for GPU configurations + cost estimates, or use one of the hosted inference providers listed on this page.
Where can I access Nomic Embed Text?
Nomic Embed Text's access providers haven't been catalogued yet on RentGPU. Check the maker's documentation for official endpoints.
How much does it cost to run Nomic Embed Text?
Self-hosting cost depends on the GPU you rent and the throughput you need. See the Run It Yourself tab for GPU configurations and hourly cost estimates.
Is Nomic Embed Text open-source or proprietary?
Nomic Embed Text is open-weight under the Apache-2.0 license. You can download and self-host it.
Run it yourself
Cheapest hardware per quantisation.
Each row is one quantisation tier (the same weights compressed differently). Lower precision → lower VRAM → cheaper hardware, at the cost of small accuracy loss. $/hr refreshed hourly from each provider's API.
| Quantisation | Cheapest GPU config | Total VRAM | Live $/hr | tokens/sec | |
|---|---|---|---|---|---|
|
FP16
FP16 — half precision (default)
|
4 GB | — | — | Compare → | |
|
FP8
FP8 — 8-bit float (Hopper / Blackwell)
|
4 GB | — | — | Compare → | |
|
INT4
INT4 — 4-bit integer (~4× VRAM saving)
|
4 GB | — | — | Compare → |
Just need an API?
Skip the GPU rental and call a hosted endpoint instead.
See access providers on the Overview tab →
Description
About Nomic Embed Text.
Nomic Embed Text v1.5 is the most-downloaded open-weight embedding model. 137M parameters, 8K context, outperforms OpenAI's text-embedding-ada-002 on MTEB. Apache-2.0 licensed. Drop-in replacement for any RAG pipeline that wants to leave OpenAI.
Context window
How much it can remember.
8K tokens
≈ 6,144 English words
4K
32K
128K
1M
Capabilities
What it can do.
·
Vision input
·
Audio input
·
Video input
·
Function calling
·
Tool use
·
JSON mode
✓
Streaming
·
Fine-tuning