Granite-TimeSeries-TTM-R1
onlineibm-granite/granite-timeseries-ttm-v1805K params | 512 context | $0.5000 input | $1.50 output
This catalog entry maps the live `ttm-v1` deployment to IBM's official TTM-R1 family surface. TinyTimeMixer is a compact forecasting architecture built for fast zero-shot and few-shot forecasting on standard public benchmarks, with checkpoint specializations for specific context and prediction lengths rather than one universal dense model. It is the smallest and most deployment-friendly IBM checkpoint in the hosted catalog.
Model Classification
Family
TinyTimeMixer / 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
Public Monash forecasting datasets including Australian Electricity and Weather, Bitcoin, KDD Cup 2018, London Smart Meters, Saugeen River Flow, Solar, US Births, and wind datasets; IBM states R1 used about 250M public training samples.
Recommended For
- • CPU-friendly or latency-sensitive forecasting baselines
- • Fast zero-shot checks before escalating to larger TSFMs
Strengths
- • Very small checkpoints with efficient deployment characteristics
- • Useful lightweight baseline for standard public forecasting workloads
Limitations
- • Lower ceiling than larger modern TSFM families on broad zero-shot leaderboards
- • Checkpoint families are tuned around specific context and prediction settings
Capabilities
Tags
Specifications
- Parameters
- 805K
- Architecture
- TinyTimeMixer
- 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