# granite-timeseries-tspulse-r1 by IBM Granite: Open Model Source: https://savrn.com/models/granite-timeseries-tspulse-r1 Markdown alternate of the page above; the site index is https://savrn.com/llms.txt --- ## Runs On What it takes to serve granite-timeseries-tspulse-r1 (1M 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 | 0.0 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 | | 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 12, 2026. [granite-timeseries-tspulse-r1 on every accelerator the SAVRN Index prices, at every precision](https://savrn.com/models/granite-timeseries-tspulse-r1/gpus) ## Model Card By IBM Granite, published under apache-2.0, revision 2e64fcdc2a06. ### Granite-TimeSeries-TSPulse-R1 Model Card Update (Mar 2026): TSPulse has been accepted at ICLR 2026. TSPulse models are ultra-compact pre-trained models for time-series data, featuring just 1M parameters and supporting GPU-free inference. Designed for versatility, TSPulse excels across a wide range of tasks including classification, anomaly detection (AD), imputation, and similarity search. At the architecture level, TSPulse introduces a novel dual-space masked reconstruction strategy that learns jointly from both time and frequency domains —- capturing complementary patterns in a unified embedding space. This is coupled with a dual-embedding disentanglement mechanism that produces both fine-grained embeddings for detailed analysis and semantic embeddings for broader understanding. These semantic embeddings are inherently robust to variations in time, magnitude, and noise, making them ideal for time-series retrieval. [Read the full model card (864 words)](https://savrn.com/models/granite-timeseries-tspulse-r1/card) ## Configuration Architecture TSPulseForReconstruction Stored precision float32 Model type tspulse ## Identity and Version Repository ibm-granite/granite-timeseries-tspulse-r1 Publisher IBM Granite Task Not stated by the source Modality Other Library granite-tsfm Parameters 1M parameters Languages Not stated by the source Revision 2e64fcdc2a06d3565dfadaf0065c0ab5055f80f2 First published 2025-06-03 Last updated 2026-03-07 ## Files and Weights 5 files, 4.7 MB in total. The weights are 1 file totalling 4.4 MB in safetensors. Weights1 file · 4.4 MB Configuration1 file · 3.5 KB Documentation1 file · 9.2 KB Other1 file · 295.3 KB Repository1 file · 1.6 KB Every file | File | Type | Size | SHA-256 | | --- | --- | --- | --- | | model.safetensors | Weights | 4.4 MB | 57fa03b67d14 | | config.json | Configuration | 3.5 KB | — | | README.md | Documentation | 9.2 KB | — | | tspulse_overview.webp | Other | 295.3 KB | 2cfc0774815e | | .gitattributes | Repository | 1.6 KB | — | ## License and Download License apache-2.0 Access Open weights, no gate Download size 4.4 MB [Download from IBM Granite](https://huggingface.co/ibm-granite/granite-timeseries-tspulse-r1) Released by IBM Granite through its official repository on Hugging Face. [Read the license](https://www.apache.org/licenses/LICENSE-2.0). ## Built From - Described by arXiv:2505.13033 ## Memory Requirements | Precision | Weights in memory | | --- | --- | | As published | 4.4 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 granite-timeseries-tspulse-r1 ### How much GPU memory does granite-timeseries-tspulse-r1 need? About 0 GB at 16-bit and 0 GB at 4-bit: the weights (1M parameters) plus a working margin. A long context needs more. ### What is the cheapest GPU to run granite-timeseries-tspulse-r1 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 granite-timeseries-tspulse-r1 commercially? Yes. granite-timeseries-tspulse-r1 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. ## IBM Granite [All models and datasets](https://savrn.com/model-publishers/ibm-granite) ## Versions - [2e64fcdc2a06](https://savrn.com/models/granite-timeseries-tspulse-r1/versions/2e64fcdc2a06) · current 2026-10-12 ## Explore More - [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 2026-10-11. - [IBM Granite website](https://www.ibm.com/granite) - [Hugging Face record](https://huggingface.co/ibm-granite/granite-timeseries-tspulse-r1) - [How the hub is built](https://savrn.com/model-hub/methodology)