FlowState
onlineibm-granite/granite-timeseries-flowstate-r19.07M params | 512 context | $0.5000 input | $1.50 output
FlowState is IBM's sampling-rate-invariant TSFM for zero-shot forecasting. Its SSM encoder and functional basis decoder let it adapt context length, target length, and sampling rate at inference time instead of being tied to a single fixed timescale. It is the right IBM model when your data arrives at inconsistent cadences or when you need one model to generalize across multiple temporal resolutions.
Model Classification
Family
FlowState / Granite TimeSeries
Type
time series foundation model
Pretrained time-series model exposed on TSFM.ai for zero-shot or few-shot forecasting workloads.
Resources
Training Data
Subsets of Gift-Eval Pretrain and the Chronos pretraining corpus, with the official card stating that the used data does not overlap Gift-Eval evaluation splits.
Recommended For
- • Forecasting across inconsistent sampling rates or timescales
- • One-model deployments spanning multiple temporal cadences
Strengths
- • Designed to generalize across varying resolutions
- • Flexible context and horizon behavior at inference time
Limitations
- • Smaller public ecosystem than the biggest mainstream TSFM families
- • Less useful if all of your series already live at one fixed cadence
Capabilities
Tags
Specifications
- Parameters
- 9.07M
- Architecture
- state space encoder with functional basis decoder
- Context length
- 512
- Max output
- 1,024
- Avg latency
- n/a
- Uptime
- n/a
- Rate limit
- n/a
- Accelerator
- NVIDIA GPU
- Regions
- Virginia, US
- License
- n/a
Pricing
- Input / 1M tokens
- $0.5000
- Output / 1M tokens
- $1.50
Performance
- Average latency
- n/a
- Availability
- n/a
- Rate limit
- n/a