mxbai edge colbert v0 17m

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

Released October 20258K context≈ 5,999 words

A compact, laser-focused retrieval specialist that uses late interaction to compare query and document tokens individually rather than collapsing everything into a single vector. At just 17M parameters it runs comfortably on edge hardware, though its ColBERT architecture means it stores multiple token embeddings per document rather than one, trading index size for retrieval precision.

Capabilities

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

Instruction Following

Moderate

Multimodal

mxbai edge colbert v0 17m

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

Released October 20258K context≈ 5,999 words

A compact, laser-focused retrieval specialist that uses late interaction to compare query and document tokens individually rather than collapsing everything into a single vector. At just 17M parameters it runs comfortably on edge hardware, though its ColBERT architecture means it stores multiple token embeddings per document rather than one, trading index size for retrieval precision.

Capabilities

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

Instruction Following

Moderate

Multimodal

Glossary

ArchitectureThe underlying structural design of a neural network that defines how data flows through layers and components.ColBERT ArchitectureA neural retrieval model design that stores multiple token-level embeddings per document and uses late interaction to achieve higher retrieval accuracy than single-vector approaches.EmbeddingsNumerical representations of text that capture semantic meaning, allowing the model to measure similarity between different words or phrases.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.ParametersThe learned numerical values in a model — more parameters generally means more capacity but higher compute cost.PrecisionThe level of numerical detail a model uses to represent its internal values; higher precision means more accurate calculations but requires more memory.RetrievalThe process of finding and returning relevant documents or information from a database based on a query.TokenA small unit of text (a word, subword, or punctuation mark) that a language model breaks input into for processing.Token EmbeddingsNumerical representations of individual words or subwords that capture their meaning and relationships in a way machines can process.TokensThe basic units of text that a language model processes, typically representing words or word fragments.

mxbai edge colbert v0 17m

Capabilities

mxbai edge colbert v0 17m

Capabilities

Use Case Fit

Similar Models

Glossary