Mixpeek offers three tiers of embedding model implementations, ranging from simplified multimodal options to custom enterprise solutions.

1. Simplified Multimodal Models

These models provide an easy-to-use interface for common modalities. Mixpeek automatically selects and updates the most performant models based on industry benchmarks.

ModalityModel IDVector SizeBenchmarksDescription
Texttext1024MTEB LeaderboardGeneral purpose text embedding
Imageimage512ImageNetVisual feature extraction
Multimodalmultimodal1024ActivityNetTemporal video understanding
Audioaudio768SUPERBAudio feature extraction
KeywordkeywordSparse-Sparse text embeddings

Example usage:

{
    "type": "text",
    "value": "search query",
    "embedding_model": "text"  # Uses the default model
}

2. Hosted Model Selection

For more control, you can specify exact model implementations:

Model IDModalitiesVector SizeTypeProvider
baai-bge-m3Text1024DenseBAAI
openai-clip-vit-base-patch32Image, Text512DenseOpenAI
naver-splade-v3TextSparseSparseNaver
vertex-multimodalImage, Video, Text1408DenseGoogle

Example usage:

{
    "type": "text",
    "value": "search query",
    "embedding_model": "baai-bge-m3"  # Specific model selection
}
Email us for help deciding which model is best for your use case at no cost: info@mixpeek.com

3. Custom Model Integration

Enterprise customers can integrate their own models:

  1. Deploy your model with a compatible API
  2. Register the model in your namespace
  3. Use your custom model ID in requests

Example configuration:

{
    "namespace": "enterprise-ns",
    "model_config": {
        "id": "custom-model-v1",
        "endpoint": "https://your-model-endpoint",
        "supported_modalities": ["text", "image"],
        "vector_size": 768
    }
}

Example usage:

# X-Namespace Header: enterprise-ns
{
    "type": "text",
    "value": "search query",
    "embedding_model": "custom-model-v1",
}

Enterprise Feature: Requires namespace configuration, email us for more info: info@mixpeek.com

Model Registry Details

Each model in the registry includes:

  • Supported modalities
  • Vector type (dense or sparse)
  • Output dimensions
  • Hosting location and provider
  • Performance metrics