Forecasting

Time-MoE

A forecasting model with a sparse architecture: only part of the network runs at each step, so it stays fast at a small size.

Developer
The Time-MoE team, not disclosed
First release
Sep 2024
Latest release
Sep 2024
Sizes
50M and 200M
License
Commercial use allowedApache 2.0
Running
On your own serverAlso runs without a GPU
Industries
Retail and marketplaces, Manufacturing and logistics, Finance, Software development
Deploy on your server Hugging Face GitHub

What it does

  • Forecasting sales and stock levels
  • Forecasting load on services and staff
  • Planning purchases from history

Where it is used

E-commerceManufacturing and logisticsFinance and analytics

Hardware requirements

LaptopLaptop or regular PC, up to 8 GB of VRAM — smaller versions
fits
1 GPUOne GPU with 16–80 GB — mid-size versions
no versions
ClusterServer with several GPUs — flagship versions
no versions

Versions

  1. TimeMoE-50M и TimeMoE-200M

How to run it

On your own serverWeights are downloaded from Hugging Face and served with vLLM (load and API) or llama.cpp (modest hardware). The model then runs in a closed network with no per-request fees.Hugging Face
How much hardware you needCalculate the VRAM for the model size, context length and number of concurrent requests.Open the hardware calculator

I can set this up end to end: pick the model size, deploy it on your server and connect it to your systems.

Frequently asked questions

Can Time-MoE be used in a commercial project?

Yes. License: Apache 2.0. It allows commercial use, but it is still worth having a lawyer review the license before launch.

What hardware does Time-MoE need?

At minimum: Laptop or regular PC, up to 8 GB of VRAM — smaller versions. Some versions also run on an ordinary CPU, without a GPU. You can calculate the exact VRAM for your model size and context in the hardware calculator.

Does Time-MoE support Russian?

Language does not matter for this model: it does not work with text.

Where can I download Time-MoE and what does it cost?

The Time-MoE weights are open and free to download. You only pay for the hardware it runs on and for the setup. Source links are at the bottom of this page.

How I deploy it for clients

  1. SelectionI pick the model size for your task and hardware and test it on your examples.
  2. DeploymentI deploy it on your server or in a closed network and provide an API.
  3. Fine-tuningI fine-tune it on your data (LoRA) or connect a knowledge base — whichever is cheaper for the task.
  4. IntegrationI connect it to your CRM, ERP, bot, website or team chat and set up monitoring.

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DetailsForecastingTimesFMGoogle · USACommercial use with conditions

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DetailsForecastingMoiraiSalesforce · USANon-commercial only

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Details

Source: huggingface.co/Maple728/TimeMoE-200M. Data checked against the model card on 22 Sep 2026. Have a lawyer review the license before commercial launch.