time seriesfamily
Time-LLM
Method that reprograms a frozen large language model to forecast time series (ICLR 2024). Paper by Jin et al. (2023).
Levelfamily
Classtime series
Parametersnot in the notes
Contextnot in the notes
Released3 Oct 2023
Opennessopen source
Runs onnot in the notes
Statusactive
R&D Topics
Identity
- Developer
- Monash University, Ant Group
- Family
- not in the notes
- Released
- 3 Oct 2023 sourcesannouncement page
- Weights published
- –
- Record checked
- 12 Oct 2026
Where this comes from
Developer and dates from the research notes. Release date is the vendor's public announcement; weights date is when open weights were published.
Architecture and Size
- Architecture
- dense transformer Reprograms a frozen large language model for forecasting
- Total parameters
- – sources
- Active parameters
- –
- Checkpoint parameters
- –
- Context length
- not in the notes
- Input
- time series
- Output
- time series
Where this comes from
Parameter counts as the developer states them. Where the checkpoint holds a different total, both are shown (register A16).
Openness and Access
- Openness
- open source
- Licence
- Apache License 2.0 sources
- Access routes
- not in the notes
Where this comes from
The licence file governs over registry tags and aggregator labels.
Deployment
- Runs on
- not in the notes
- Footprint
- Licence is that of the official KimMeen/Time-LLM repository (Apache-2.0).
- Runtimes
- not in the notes
Where this comes from
Deployment tiers and runtimes as named in the notes. Footprint is the notes' figure, not a measurement by AURION.
Indonesia
- Indonesian support
- not stated
- Regional languages
- not in the notes
- Jakarta hosting
- unknown
- Languages
- not in the notes
Where this comes from
Indonesia fields are carried on every model; unknown is an allowed value.
Benchmark Results
The notes record no benchmark result for this model.
Lineage
The notes record no lineage for this model.
Industry Use Cases
No industry use case links this model.
Links
ModelTime-LLMMonash University, time series
Time-LLMMonash University, time seriesR&D TopicsTime-Series Foundation Models
Use CasesIndustrial Forecasting (Load, Throughput, Demand)IndustrialDemand ForecastingRetail and LogisticsAnomaly Detection on Sensor, SCADA and Historian DataIndustrialEnergy OptimisationIndustrial+1 moreUse cases of models in the same R&D topic; none is recorded for this model itself.
Who Runs It
PT Amman Mineral Nusa Tenggara (AMMAN)In production, 8 Jul 2026
PT Pertamina Hulu Rokan (PHR)In production, 17 Oct 2025MIND IDResearch, 14 Oct 2025
Shenzhen Energy GroupIn production, 23 Jun 2025+4 moreDeployments of these use cases; none names this model.
PT Amman Mineral Nusa Tenggara (AMMAN)In production, 8 Jul 2026PT Pertamina Hulu Rokan (PHR)In production, 17 Oct 2025MIND IDResearch, 14 Oct 2025Shenzhen Energy GroupIn production, 23 Jun 2025+4 moreDeployments of these use cases; none names this model.Sources
- arxiv.org/abs/2310.01728 https://arxiv.org/abs/2310.01728
- github.com/KimMeen/Time-LLM https://github.com/KimMeen/Time-LLM
- nixtlaverse.nixtla.io/neuralforecast/docs/capabilities/overview.html https://nixtlaverse.nixtla.io/neuralforecast/docs/capabilities/overview.html
- arxiv.org/html/2310.01728 https://arxiv.org/html/2310.01728
To cite this page: Project AURION, AI Use-Cases Research & Innovation, "Time-LLM", https://aurion.semai.id/models/time-llm/, records of October 2026.