TimeGEN-1
timegen-1
Last refreshed 2026-05-16. Next refresh: weekly.
TimeGEN-1 is worth evaluating for general LLM work when its provider route and context window match the workload.
Decision context: Coding task fit, 1 tracked provider route, and research from 2026-05-16.
Use it for
- Teams evaluating general LLM work
- Buyers comparing 1 tracked provider route
Do not use it for
- Vision or document-understanding workloads
- Strict JSON or tool-calling flows
Cheapest output
-
Microsoft Foundry per 1M tokens
Provider routes
1
Tracked API hosts
Quality / dollar
Unknown
No task benchmark coverage yet
Freshness
2026-05-16
Researched today
Top use-case fit
No primary decision-task fit is mapped for this model yet.
Provider price ladder
| Provider | Input / 1M | Output / 1M | Route |
|---|---|---|---|
| Microsoft Foundry | - | - | ServerlessPartial |
Benchmark peer barsfor Coding
No task-mapped benchmark peers are available for this model yet.
Migration checks
No linked migration route is available for this model yet.
About
TimeGEN-1 is Nixtla's generative pre-trained forecasting and anomaly detection model for time series data. It can produce accurate forecasts for new time series without training, using only historical values and exogenous covariates as inputs. Available on Azure AI Foundry; requires Nixtla's custom inference API.
Capabilities
No model capability flags are currently sourced.