# NVIDIA — NVIDIA Nemotron 3.5 Embed, Rerank, and Parse: Advancing Agents with World-Class Retrieval Models

- Company: NVIDIA (nvidia.com)
- Announced: 2026-10-21T10:41:36+00:00
- Category: new-model
- Coverage: not counted
- Announcement: yes
- Group: models
- Source: https://huggingface.co/blog/nvidia/nemotron-retriever-world-class-agentic-retrieval
- Record: https://forck.live/items/25818-nvidia-nemotron-3-5-embed-rerank-and-parse-advancing-agents-with-world-class
- Open weights: yes
- Models affected: Nemotron 3.5 Embed 8B BF16, Nemotron 3.5 Embed 1B BF16, Nemotron 3.5 Embed 1B NVFP4, Nemotron 3.5 Rerank 8B BF16, Nemotron 3.5 Parse, Nemotron 3 Embed, Llama Nemotron Embed VL 1B

NVIDIA expanded its Nemotron Retriever collection with open, commercially available models for embedding, reranking and document extraction, aimed at cutting the tokens agents waste on repeated searches. The release covers Nemotron 3.5 Embed in 8B BF16, 1B BF16 and 1B NVFP4 variants, Nemotron 3.5 Rerank 8B BF16, and Nemotron 3.5 Parse at 631M parameters. NVIDIA says adding Nemotron 3.5 Rerank cut agentic token cost per query by roughly 14% with the 8B embedder and 13% with the 1B, while improving retrieval accuracy in both setups. With the 8B retriever, the reranker scored about 0.9 points higher nDCG@10 than Qwen3-VL-Reranker-8B at similar token cost. On ViDoRe v3.1, Nemotron 3.5 Embed 8B BF16 reached 61.17 nDCG@10, which NVIDIA says ranked first among dense retrieval models as of 10/20/2026, an 8.94-point gain over Llama Nemotron Embed VL 1B. The 1B model, distilled from the 8B teacher, scores 58.38 nDCG@10 and retains 95.4% of the teacher's score, and on MIRACL Vision the 8B model reaches 72.6 nDCG@10, 4.3 points above Qwen3-VL-Embedding-8B.

## Evidence

Verbatim from https://huggingface.co/blog/nvidia/nemotron-retriever-world-class-agentic-retrieval:

> Adding Nemotron 3.5 Rerank reduces agentic token cost per query by approximately 14% with Nemotron 3.5 Embed 8B, and 13% with Nemotron 3.5 Embed 1B, while improving retrieval accuracy in both configurations.

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