nvidia
NVIDIA: Nemotron 3.5 Embed 8B (free)
nvidia/nemotron-3.5-embed-8b:free
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
According to OpenRouter’s catalog, nvidia/nemotron-3.5-embed-8b:free is an NVIDIA embedding variant that accepts text and image inputs and returns embeddings. The catalog describes it for multilingual retrieval involving text queries and document page images such as tables, charts, and infographics, with a 32,768-token context window. It is listed as a free variant. These are catalog-reported capabilities, not verified performance; no independent model card or measured benchmark evidence was included in this source pack.[1]
Strengths
Limitations
- Evidence comes only from OpenRouter’s catalog; an independent model card was not available in this source pack.[1]
- No measured benchmark results are supplied, so retrieval quality, speed, and reliability require workload-specific validation.[1]
- License, hardware, safety, and API parameter support details are not established by the evidence.[1]
Where to use it
- Evaluate it for semantic indexing and retrieval systems that need shared embeddings for text and document page images.[1]
- Consider it for multilingual document-search prototypes where pages contain tables, charts, or infographics.[1]
- Test it where a long context window may matter, while confirming the catalog-reported 32,768-token limit in the target workload.[1]
Sources
- [1] OpenRouter catalog · NVIDIA: Nemotron 3.5 Embed 8B (free)Sources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
Nemotron 3.5 Embed 8B is a multimodal embedding model from NVIDIA for multilingual retrieval over text and document page images (tables, charts, infographics). Queries are text and documents can be...
Specifications
- Model ID
- nvidia/nemotron-3.5-embed-8b:free
- Canonical ID
- nvidia/nemotron-3.5-embed-8b-20261021
- Creator
- nvidia
- Added to OpenRouter
- 21.10.2026
- Context length
- 32,768
- Modality
- text+image->embeddings
- Input modalities
- text, image
- Output modalities
- embeddings
- Token pricing
- USD per 1M tokens: in $0 / out $0
- Knowledge cutoff
- —
- Expiration date
- —
Tasks and capabilities
A grade appears only where the source supplies a matching measurement for that task, the model is active and the cohort holds at least 10 comparable models. The capability column lists facts the source declares — supported formats, reasoning and tool parameters — which are not measured quality.
| Task | Grade | Source-declared capability |
|---|---|---|
| General quality | No measurement | — |
| Coding | No measurement | — |
| Agents | No measurement | — |
| Writing | No measurement | — |
| Reasoning | No measurement | — |
| Document analysis | No measurement | — |
| Vision | No measurement | input: image |
| Image generation | No measurement | — |
| Audio | No measurement | — |
| Video | No measurement | — |
| Embeddings | No measurement | output: embeddings |
Evaluations
No evaluations are supplied for this model.
How grades work
Each letter grade compares a model only against other models scored by the same source and metric in the current snapshot. S means the top 10%, A the next 20%, B the next 30%, C the rest. Models without a published measurement are shown as not rated — a supported format alone never implies measured quality.
- S — S — top 10% of the cohort
- A — A — next 20% of the cohort
- B — B — next 30% of the cohort
- C — C — below the B band
Providers
Optional live provider statistics from OpenRouter. Missing values are unknown, not zero.
| Provider | Context length | Price in /1M | Price out /1M | Latency p50 (30m, s) | Throughput p50 (30m, tok/s) | Uptime (30m) |
|---|---|---|---|---|---|---|
| Nvidiabf16 | 32,768 | $0 | $0 | — | — | 100% |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.