Kairos-23M
Model directorymldi-lab/Kairos_23m23M params | Upstream checkpoint
Kairos-23M is the mid-size public Kairos checkpoint from the Ant Group and ShanghaiTech University Kairos release. It sits in the middle of the Kairos size ladder, offering more capacity than the 10M model for broader zero-shot coverage while staying well below the 50M checkpoint.
Like the rest of the family it is an encoder-decoder transformer built around adaptive tokenization and instance-adaptive rotary position encoding, so it varies both patching granularity and positional treatment to match each series' information density and temporal structure. It is pretrained on the PreSTS corpus of 300B+ time points, the same source that gives the family its broad cross-domain zero-shot reach.
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Hugging Face provider mappings checked 2026-10-06. No Inference Provider mapping was listed for this checkpoint.
Model Classification
Family
Kairos
Type
time series foundation model
Pretrained time-series model for zero-shot or few-shot forecasting workloads.
Resources
Training Data
PreSTS corpus with 300B+ time points, as documented by the official Kairos model cards and project page.
Recommended For
- • Adaptive zero-shot forecasting across heterogeneous series
- • Teams that want a mid-size open family with modern tokenization ideas
Strengths
- • Adaptive tokenization handles changing information density well
- • Clear parameter-size ladder from small to larger public checkpoints
Limitations
- • Newer family with a smaller production footprint than the most established lines
- • Focused on forecasting rather than general multi-task time-series tooling
Capabilities
Tags
Specifications
- Parameters
- 23M
- Architecture
- encoder-decoder transformer with adaptive patching and instance-adaptive rotary position encoding
- Context length
- n/a
- Max context
- n/a
- Minimum history
- n/a
- Recommended history
- n/a
- Input step
- n/a
- Required target series
- 1
- Temperature
- Ignored
- Top P
- Ignored
- Max output
- n/a
- License
- n/a