Describe a model
You can use hosted models as an integrated part of Pinecone operations or for standalone embedding and reranking. For more details, see Vector embedding and Rerank results.
PINECONE_API_KEY="YOUR_API_KEY"
curl "https://api.pinecone.io/models/llama-text-embed-v2" \
-H "Api-Key: $PINECONE_API_KEY" \
-H "X-Pinecone-Api-Version: 2025-10"{
"model": "llama-text-embed-v2",
"short_description": "A high performance dense embedding model optimized for multilingual and cross-lingual text question-answering retrieval with support for long documents (up to 2048 tokens) and dynamic embedding size (Matryoshka Embeddings).",
"type": "embed",
"vector_type": "dense",
"default_dimension": 1024,
"modality": "text",
"max_sequence_length": 2048,
"max_batch_size": 96,
"provider_name": "NVIDIA",
"supported_metrics": [
"Cosine",
"DotProduct"
],
"supported_dimensions": [
384,
512,
768,
1024,
2048
],
"supported_parameters": [
{
"parameter": "input_type",
"required": true,
"type": "one_of",
"value_type": "string",
"allowed_values": [
"query",
"passage"
]
},
{
"parameter": "truncate",
"required": false,
"default": "END",
"type": "one_of",
"value_type": "string",
"allowed_values": [
"END",
"NONE",
"START"
]
},
{
"parameter": "dimension",
"required": false,
"default": 1024,
"type": "one_of",
"value_type": "integer",
"allowed_values": [
384,
512,
768,
1024,
2048
]
}
]
}GET /models/{model_name}
Parameters
Section titled “Parameters”X-Pinecone-Api-Version(header, string, required) — Required date-based version headermodel_name(path, string, required) — The name of the model to look up.
Responses
Section titled “Responses”200— The model details.401— Unauthorized. Possible causes: Invalid API key.404— Model not found.500— Internal server error.