ANEMLL VibeThinker 1.5B — Variable Context State Transition Model v0.3.5
Open Source
Infrastructure
The ANEMLL VibeThinker 1.5B is a machine learning model optimized for the Apple Neural Engine (ANE), enabling efficient on-device inference with dynamic context size support. It demonstrates variable context inference by starting with a small key-value (KV) cache and automatically expanding it as the output length increases, allowing for the generation of outputs exceeding 24,000 tokens on devices with a 4,096-token context model.
Optimized for Apple Neural Engine (ANE)
Supports dynamic context sizes up to 4,096 tokens
Enables on-device inference with outputs over 24,000 tokens