ai/snowflake-arctic-embed-l-v2-vllm repository overview

⁠Snowflake's Arctic-embed-l-v2.0

Snowflake arctic-embed-l-v2.0 is the newest addition to the suite of embedding models Snowflake has released optimizing for retrieval performance and inference efficiency. Arctic Embed 2.0 introduces a new standard for multilingual embedding models, combining high-quality multilingual text retrieval without sacrificing performance in English. Released under the permissive Apache 2.0 license, Arctic Embed 2.0 is ideal for applications that demand reliable, enterprise-grade multilingual search and retrieval at scale.

⁠📌 Characteristics

⁠🐳 Using this model with Docker Model Runner

First, pull the model:

docker model pull ai/snowflake-arctic-embed-l-v2-vllm

Then run the model:

curl --location 'http://localhost:12434/engines/vllm/v1/embeddings' \
--header 'Content-Type: application/json' \
--data '{
    "model": "ai/snowflake-arctic-embed-l-v2-vllm",
    "input": "hello world!"
  }'

For more information, check out the Docker Model Runner docs⁠.

⁠MTEB (Multilingual)

Unlike most other open-source models, Arctic-embed-l-v2.0 excels across English (via MTEB Retrieval) and multilingual (via MIRACL and CLEF). You no longer need to support models to empower high-quality English and multilingual retrieval. All numbers mentioned below are the average NDCG@10 across the dataset being discussed.

⁠🔗 Links

• Technical Report⁠
• Hugging Face Model Card⁠