magi

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

Released January 2024context N/A

Magi is a text embedding model that converts input text into dense vector representations. It operates quietly in the background — no chat, no generation, just focused encoding work. Its open-weight nature means the internals are fully inspectable and deployable without API dependencies.

Capabilities

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

Tool Use

Moderate

Reasoning & Logic

Moderate

Creative Writing

Use Case Fit

Fit scores are AI-generated based on model capabilities, intended use, and technical specifications. Learn more

magi

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

Released January 2024context N/A

Magi is a text embedding model that converts input text into dense vector representations. It operates quietly in the background — no chat, no generation, just focused encoding work. Its open-weight nature means the internals are fully inspectable and deployable without API dependencies.

Capabilities

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

Tool Use

Moderate

Reasoning & Logic

Moderate

Creative Writing

Use Case Fit

Fit scores are AI-generated based on model capabilities, intended use, and technical specifications. Learn more

Glossary

APIAn interface that allows developers to send requests to and receive responses from an AI model over the internet.Dense VectorA compact numerical representation where most values are non-zero, used to efficiently store and compare the meaning of text.EmbeddingA dense numerical vector that represents a word, sentence, or concept in a high-dimensional space.Embedding ModelA model that converts text into numerical vectors that capture semantic meaning, allowing computers to understand and compare the similarity between different pieces of text.Text EmbeddingA technique that converts text into numerical vectors that capture semantic meaning, allowing the model to understand and compare text similarity.Text Embedding ModelA neural network that converts text into numerical vectors that capture semantic meaning, allowing computers to understand and compare text similarity.