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Chronos
Chronos is a collection of pretrained time series forecasting models that produce probabilistic forecasts from historical data.
Chronos provides an interface to a family of pretrained time series forecasting models based on language model architectures. Users generate probabilistic forecasts by inputting historical context, which the models interpret through scaling and quantization into sequences of tokens. The library supports various configurations, including the high-performance Chronos-2, which handles univariate, multivariate, and covariate-informed forecasting. Chronos-Bolt variants use patch-based methods to increase speed and memory efficiency significantly compared to the original models. These models are designed for researchers and developers requiring automated forecasting capabilities without extensive retraining.
Chronos at a glance
Key features
- Zero-shot forecasting for univariate and multivariate tasks
- Support for covariate-informed forecasting
- Direct multi-step forecasting via patch-based processing
- Probabilistic forecast generation through trajectory sampling
- Integration with AWS SageMaker and AutoGluon-Cloud
- Compatible with CPU and GPU inference endpoints
Use it for
- Predicting future time series values from historical data
- Benchmarking forecasting model performance
- Deploying real-time, serverless, or batch inference pipelines
- Generating forecasts using pretrained model variants
Alternatives to Chronos
- Nixtla TimeGPT — Foundational model for forecasting and anomaly detection.
- FoundationForecast — Unifies multiple time series foundation models under one single API and data format.
- FinCatch Studio — Simulates forward scenarios and stress-tests financial models on primary facts.
- PreReason — Delivers financial market briefings with the interpretation already done.
- FinGPT — Access open-source financial language models and APIs at a low cost.
- NanoJev — It runs parallel decisions and outputs probability distributions without output-token decoding.
- Auto Deep Researcher — Automates experiment operations to reduce manual babysitting of training loops.
- Tick Stock Panel — Runs in a single Docker container with local Parquet storage and zero external databases.
- Finetuning With Sampling — Official implementation of the Finetuning with Sampling research paper from Harvard.
- Ncm — Generates text significantly faster than diffusion baselines while maintaining high quality.
- Tegus — Access 300,000+ expert transcripts and 4,000+ financial models in one platform.
- PageIndex — It provides 98.7% accuracy on FinanceBench without vector databases.
All Chronos alternatives