nvidia
NVIDIA: Nemotron 3.5 Rerank 8B (free)
nvidia/nemotron-3.5-rerank-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-rerank-8b:free is an NVIDIA reranking model that accepts text and image inputs and returns reranking output. The catalog reports a 32,768-token context length, but this source pack contains no independent model card, description, benchmark measurements, supported request parameters, license terms, or deployment requirements. It may therefore be worth evaluating for retrieval or search reranking, especially multimodal pipelines, while treating quality, latency, and production fit as unverified until workload testing.[1]
Strengths
Limitations
- The only supplied evidence is an OpenRouter catalog record; an independent model card was not available in this source pack, so capabilities are catalog-reported rather than independently documented.[1]
- No measured quality, latency, benchmark, or comparative ranking evidence was supplied; validate the model on representative queries, documents, and images before relying on it.[1]
- The catalog leaves the description, supported parameters, knowledge cutoff, Hugging Face identifier, and expiration date unset or empty, leaving operational behavior and integration options unclear.[1]
Where to use it
- Consider it for the reranking stage in retrieval or search systems that reorder candidate items, pending in-domain relevance testing.[1]
- Consider it for multimodal search or media retrieval where text and image inputs require rerank output rather than generated text, after confirming the intended payload shape.[1]
Sources
- [1] OpenRouter catalog · NVIDIA: Nemotron 3.5 Rerank 8B (free)Sources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
The source does not supply a description for this model.
Specifications
- Model ID
- nvidia/nemotron-3.5-rerank-8b:free
- Canonical ID
- nvidia/nemotron-3.5-rerank-8b-20261021
- Creator
- nvidia
- Added to OpenRouter
- 21.10.2026
- Context length
- 32,768
- Modality
- text+image->rerank
- Input modalities
- text, image
- Output modalities
- rerank
- Token pricing
- No per-token price in the source snapshot — see OpenRouter for the billing unit
- 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 | — |
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 | — | — | — | — | 100% |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.