mxbai edge colbert v0 32m

Open WeightModel weights are publicly available — can be downloaded and self-hosted

Released October 20258K context≈ 5,999 words

A compact, retrieval-focused specialist that uses ColBERT's late interaction mechanism to compare query and document tokens individually rather than collapsing everything into a single vector. At 32M parameters it runs efficiently on edge devices, making it practical for on-device search pipelines. The trade-off is narrow scope — it produces embeddings, not text, and is purpose-built for retrieval rather than general-purpose understanding.

Capabilities

Capability scores are AI-generated based on model documentation, benchmarks, and technical specifications. Learn more

Long Context

Moderate

Factual Knowledge

mxbai edge colbert v0 32m

Open WeightModel weights are publicly available — can be downloaded and self-hosted

Released October 20258K context≈ 5,999 words

A compact, retrieval-focused specialist that uses ColBERT's late interaction mechanism to compare query and document tokens individually rather than collapsing everything into a single vector. At 32M parameters it runs efficiently on edge devices, making it practical for on-device search pipelines. The trade-off is narrow scope — it produces embeddings, not text, and is purpose-built for retrieval rather than general-purpose understanding.

Capabilities

Capability scores are AI-generated based on model documentation, benchmarks, and technical specifications. Learn more

Long Context

Moderate

Factual Knowledge

Glossary

EmbeddingsNumerical representations of text that capture semantic meaning, allowing the model to measure similarity between different words or phrases.General-PurposeDesigned to handle a wide variety of different tasks rather than being specialized for one specific domain.Late InteractionA retrieval technique that compares individual tokens between a query and document separately, then combines the results, rather than comparing pre-computed single vectors.On-DeviceA model designed to run directly on a user's device (phone, laptop, etc.) rather than requiring a remote server.ParametersThe learned numerical values in a model — more parameters generally means more capacity but higher compute cost.RetrievalThe process of finding and returning relevant documents or information from a database based on a query.Retrieval-FocusedA model specifically trained to find and rank relevant documents or passages in response to search queries, rather than generate new text.TokensThe basic units of text that a language model processes, typically representing words or word fragments.

Capabilities

Capabilities

Use Case Fit

Glossary