Embedding model for semantic search, retrieval, clustering, and ranking pipelines
- Context
- 33K
- Released
- 8mo ago
- Parameters
- 1B
Sources:models.dev
Benchmarks
DeepSWE is the primary coding benchmark where an exact model evaluation exists. Other sourced evaluations appear below; missing scores are not zero.
Not evaluated in DeepSWE 1.1 as of 2026-09-22. Results are only shown for exact model versions in the official dataset. Official leaderboard.
No benchmark results have been matched to this model yet.
Specifications
- Developer
- NVIDIA
- Model family
- —
- Type
- Language model
- Predecessor
- —
- Successor
- —
- Released
- February 10, 2026
- Model ID
nvidia/llama-nemotron-embed-vl-1b-v2- Openness
- Open weights
- License
- —
- Parameters
- 1B
- Input modalities
- text, image
- Output modalities
- text
- Modality
- text+image->text
- Max output tokens
- 2K
- Hugging Face
- —
- Source freshness
- Metadata synced Oct 8, 2026, 10:17 PM UTC
Additional source evidence
- Source model
- nvidia/llama-nemotron-embed-vl-1b-v2
- Source family
- nemotron
- Last updated
- 2026-02-10
- Model context
- 33K
- Model output limit
- 2K
- Open weights
- Yes
- File attachments
- Yes
- Reasoning
- No
- Tool calling
- No
- Temperature control
- No
Complete source record (JSON)
{
"id": "nvidia/llama-nemotron-embed-vl-1b-v2",
"name": "Llama Nemotron Embed VL 1B v2",
"description": "Embedding model for semantic search, retrieval, clustering, and ranking pipelines",
"family": "nemotron",
"last_updated": "2026-02-10",
"attachment": true,
"reasoning": false,
"tool_call": false,
"temperature": false,
"modalities": {
"input": [
"text",
"image"
],
"output": [
"text"
]
},
"limit": {
"context": 32768,
"output": 2048
},
"release_date": "2026-02-10",
"open_weights": true
}Infrastructure
Provider availability
Provider endpoint data will appear after this model's first OpenRouter endpoint sync.
Deployment graph
Can I run this?
Vertical Tabs only shows compatibility when it has structured evidence tying this exact model to hardware, runtime, quantization, memory use, and observed performance.