# chronos-bolt-mini by Amazon: Open-Weight Model Source: https://savrn.com/models/chronos-bolt-mini-2 Markdown alternate of the page above; the site index is https://savrn.com/llms.txt --- ## Runs On What it takes to serve chronos-bolt-mini (21M parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them. | Precision | Weights | Memory needed | Cheapest setup | Per hour | Also fits | | --- | --- | --- | --- | --- | --- | | 16-bit | 0.0 GB | 0.1 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/mi325x) $2.00 | | 8-bit | 0.0 GB | 0.0 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/mi325x) $2.00 | | 4-bit | 0.0 GB | 0.0 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/mi325x) $2.00 | Memory is the weights at that precision plus 20% for the runtime and a short context; a long context needs more. Prices are the lowest on-demand hourly rates in the [SAVRN Index](https://savrn.com/ai-index/pricing/gpus), read Oct 24, 2026. [chronos-bolt-mini on every accelerator the SAVRN Index prices, at every precision](https://savrn.com/models/chronos-bolt-mini-2/gpus) ## SAVRN's Notes on chronos-bolt-mini Chronos-Bolt is Amazon's fast forecasting family: give it a history, get a forecast, with no training on your data. The mini model has 21M parameters, small enough to forecast thousands of series on a CPU, which is where most forecasting actually runs. Apache 2.0 allows commercial use, and the model is also offered through Amazon SageMaker if you prefer a managed endpoint. Start with it as a baseline for demand, capacity or energy series. If accuracy falls short, move up the Bolt sizes before you reach for the original, slower Chronos T5 models. SAVRN Research, 2026-09-18 ## Model Card By Amazon, published under apache-2.0, revision 251268337516. Update Feb 14, 2025: Chronos-Bolt models are now available on Amazon SageMaker JumpStart! Check out the [tutorial notebook](https://github.com/amazon-science/chronos-forecasting/blob/main/notebooks/deploy-chronos-to-amazon-sagemaker.ipynb) to learn how to deploy Chronos endpoints for production use in a few lines of code. Chronos-Bolt is a family of pretrained time series forecasting models which can be used for zero-shot forecasting. It is based on the [T5 encoder-decoder architecture](https://savrn.com/papers/exploring-the-limits-of-transfer-learning-with-a-unified-text-to-text-transformer) and has been trained on nearly 100 billion time series observations. It chunks the historical time series context into patches of multiple observations, which are then input into the encoder. The decoder then uses these representations to directly generate quantile forecasts across multiple future steps—a method known as direct multi-step forecasting. Chronos-Bolt models are up to 250 times faster and 20 times more memory-efficient than the [original Chronos](https://savrn.com/papers/chronos-learning-the-language-of-time-series) models of the same size. ### Performance [Read the full model card (835 words)](https://savrn.com/models/chronos-bolt-mini-2/card) ## Configuration Architecture ChronosBoltModelForForecasting Vocabulary size 2 Stored precision float32 Model type t5 ## Identity and Version Repository amazon/chronos-bolt-mini Publisher Amazon Task Time series forecasting Modality Time series Library chronos-forecasting Parameters 21M parameters Languages Not stated by the source Revision 251268337516a88e253628c43e1d26ec577b376b First published 2024-11-25 Last updated 2025-11-21 ## Files and Weights 4 files, 85.0 MB in total. The weights are 1 file totalling 85.0 MB in safetensors. Weights1 file · 85.0 MB Configuration1 file · 1.1 KB Documentation1 file · 8.7 KB Repository1 file · 1.5 KB Every file | File | Type | Size | SHA-256 | | --- | --- | --- | --- | | model.safetensors | Weights | 85.0 MB | 1a1a4297f132 | | config.json | Configuration | 1.1 KB | — | | README.md | Documentation | 8.7 KB | — | | .gitattributes | Repository | 1.5 KB | — | ## License and Download License apache-2.0 Access Open weights, no gate Download size 85.0 MB [Download from Amazon](https://huggingface.co/amazon/chronos-bolt-mini) Released by Amazon through its official repository on Hugging Face. [Read the license](https://www.apache.org/licenses/LICENSE-2.0). ## Built From - Described by [arXiv:1910.10683](https://savrn.com/papers/exploring-the-limits-of-transfer-learning-with-a-unified-text-to-text-transformer) - Described by [arXiv:2403.07815](https://savrn.com/papers/chronos-learning-the-language-of-time-series) ## Memory Requirements | Precision | Weights in memory | | --- | --- | | As published | 85.0 MB | | 16-bit | 0.0 GB | | 8-bit | 0.0 GB | | 4-bit | 0.0 GB | Weights only, from the published parameter count; the key-value cache and runtime add to this. ## Questions About chronos-bolt-mini ### How much GPU memory does chronos-bolt-mini need? About 0.1 GB at 16-bit and 0 GB at 4-bit: the weights (21M parameters) plus a working margin. A long context needs more. ### What is the cheapest GPU to run chronos-bolt-mini on? At 16-bit, 1x MI300X from $1.85 an hour; at 4-bit, 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists. ### Can I use chronos-bolt-mini commercially? Yes. chronos-bolt-mini is released under Apache License 2.0. The Apache License 2.0 is a permissive open-source license. It permits commercial use, modification and redistribution. It requires keeping the license and copyright notices and any NOTICE file, stating significant changes, and it includes an express patent grant from contributors. ## Similar Models Model · Time series forecasting ### [chronos-bolt-mini](https://savrn.com/models/chronos-bolt-mini) [Autogluon](https://savrn.com/model-publishers/autogluon) Update Feb 14, 2025: Chronos-Bolt models are now available on Amazon SageMaker JumpStart! Check out the tutorial notebook to learn how to deploy Chronos endpoints for production use in a few lines of code. Chronos-Bolt is a family of pretrained time series forecasting models which can be used for zero-shot forecasting. It is based on the T5 encoder-decoder architecture and has been trained on nearly 100 billion time series observations. It chunks the historical time series context into patches of multiple observations, which are then input into the encoder. The decoder then uses these representations to directly generate quantile forecasts across multiple future steps—a method known as… Open weights apache-2.0 21M parameters [View model](https://savrn.com/models/chronos-bolt-mini) Model · Time series forecasting ### [Toto-2.0-22m](https://savrn.com/models/toto-2-0-22m) [Datadog](https://savrn.com/model-publishers/datadog) Toto (Time Series Optimized Transformer for Observability) is a family of time series foundation models for multivariate forecasting developed by Datadog. Toto 2.0 is the current generation, featuring u-μP-scaled transformers ranging from 4m to 2.5B parameters, all trained from a single recipe. Forecast quality improves reliably with parameter count across the family. The family sets a new state of the art on three forecasting benchmarks: BOOM, our observability benchmark; GIFT-Eval, the standard general-purpose benchmark; and the recent contamination-resistant TIME benchmark. Inference code is available on GitHub. For more examples, see the Quick Start notebook and GluonTS integration… Open weights apache-2.0 22M parameters pytorch [View model](https://savrn.com/models/toto-2-0-22m) Model · Time series forecasting ### [chronos-t5-mini](https://savrn.com/models/chronos-t5-mini) [Autogluon](https://savrn.com/model-publishers/autogluon) Update Feb 14, 2025: Chronos-Bolt & original Chronos models are now available on Amazon SageMaker JumpStart! Check out the tutorial notebook to learn how to deploy Chronos endpoints for production use in a few lines of code. Update Nov 27, 2024: We have released Chronos-Bolt models that are more accurate (5% lower error), up to 250 times faster and 20 times more memory-efficient than the original Chronos models of the same size. Check out the new models here. Chronos is a family of pretrained time series forecasting models based on language model architectures. A time series is transformed into a sequence of tokens via scaling and quantization, and a language model is trained on these… Open weights apache-2.0 20M parameters transformers [View model](https://savrn.com/models/chronos-t5-mini) Model · Time series forecasting ### [chronos-t5-mini](https://savrn.com/models/chronos-t5-mini-2) [Amazon](https://savrn.com/model-publishers/amazon) Update Feb 14, 2025: Chronos-Bolt & original Chronos models are now available on Amazon SageMaker JumpStart! Check out the tutorial notebook to learn how to deploy Chronos endpoints for production use in a few lines of code. Update Nov 27, 2024: We have released Chronos-Bolt models that are more accurate (5% lower error), up to 250 times faster and 20 times more memory-efficient than the original Chronos models of the same size. Check out the new models here. Chronos is a family of pretrained time series forecasting models based on language model architectures. A time series is transformed into a sequence of tokens via scaling and quantization, and a language model is trained on these… Open weights apache-2.0 20M parameters chronos-forecasting [View model](https://savrn.com/models/chronos-t5-mini-2) Model · Time series forecasting ### [Kronos-small](https://savrn.com/models/kronos-small) [ShiYu](https://savrn.com/model-publishers/neoquasar) Kronos is the first open-source foundation model for financial candlesticks (K-lines), trained on data from over 45 global exchanges. It is designed to handle the unique, high-noise characteristics of financial data. Kronos is a family of decoder-only foundation models, pre-trained specifically for the "language" of financial markets—K-line sequences. It leverages a novel two-stage framework: 1. A specialized tokenizer first quantizes continuous, multi-dimensional K-line data (OHLCV) into hierarchical discrete tokens. 2. A large, autoregressive Transformer is then pre-trained on these tokens, enabling it to serve as a unified model for diverse quantitative tasks. The success of large-scale… Open weights mit 25M parameters [View model](https://savrn.com/models/kronos-small) Model · Time series forecasting ### [chronos-2-small](https://savrn.com/models/chronos-2-small) [Autogluon](https://savrn.com/model-publishers/autogluon) This is the small variant of the Chronos-2 model with 28M parameters. For usage and details on the Chronos-2 model, please refer to https://huggingface.co/autogluon/chronos-2. If you find Chronos-2 useful for your research, please consider citing the associated paper Open weights apache-2.0 28M parameters chronos-forecasting [View model](https://savrn.com/models/chronos-2-small) ## Amazon [All models and datasets](https://savrn.com/model-publishers/amazon) ## Versions - [251268337516](https://savrn.com/models/chronos-bolt-mini-2/versions/251268337516) · current 2026-09-18 ## Explore More - [All time series forecasting models](https://savrn.com/models/tasks/time-series-forecasting) - [All models under apache-2.0](https://savrn.com/models/licenses/apache-2-0) - [Model comparisons](https://savrn.com/models/comparisons) - [The model directory](https://savrn.com/models) - [Open model prices by host](https://savrn.com/ai-index/pricing/open-models) ## Source - Repository metadata, read 2026-10-20. - [Amazon website](https://github.com/amazon-science) - [Hugging Face record](https://huggingface.co/amazon/chronos-bolt-mini) - [How the hub is built](https://savrn.com/model-hub/methodology)