NVIDIA: llama-3_2-nemoretriever-300m-embed-v1
llama-3_2-nemoretriever-300m-embed-v1 is an embedding model from NVIDIA released on Jul 24, 2025. It reads text and writes vectors, with a 33K token context window.
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It costs $0 per million input tokens, with no charge for output.
Its weights are open, so you can host it yourself.
- Modalities
- In / out price
- $0 / $0 per 1M
- Context
- 33K
- Max output
- 2K
- Released
- Jul 24, 2025
- Knowledge cutoff
- n/a
- Tool calling
- Structured output
- Reasoning
- Prompt caching
- Open weights
- Free to use
llama-3_2-nemoretriever-300m-embed-v1 pricing
USD, as listed on Oct 15, 2026. Most bills are input heavy, so the cached input rate matters as much as the headline price.
| Input | $0 / 1M tokens | |
|---|---|---|
| Output | $0 / 1M tokens |
What llama-3_2-nemoretriever-300m-embed-v1 costs per month
Pick a workload close to yours or type your own volumes.
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llama-3_2-nemoretriever-300m-embed-v1 questions
How much does the llama-3_2-nemoretriever-300m-embed-v1 API cost?
$0 per million input tokens and $0 per million output tokens. The estimator on this page turns that into a monthly bill for your own workload.
What is the context window of llama-3_2-nemoretriever-300m-embed-v1?
32,768 tokens of input, and it can write up to 2,048 tokens in one reply. As a rough guide, a million tokens is around 750,000 English words.
Is llama-3_2-nemoretriever-300m-embed-v1 open source?
Its weights are published, so you can run it on your own hardware or a cloud of your choice. Read the license before commercial use.
When was llama-3_2-nemoretriever-300m-embed-v1 released?
Jul 24, 2025.
Catalog data from models.dev (MIT licensed), refreshed daily, last on Oct 15, 2026. The summary is written from these facts.
Building on llama-3_2-nemoretriever-300m-embed-v1?
I test your real tasks on it and the two closest alternatives, then ship the agent on whichever wins on cost and accuracy.
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