Granite-TimeSeries-TTM-R2
onlineibm-granite/granite-timeseries-ttm-r2805K params | 512 context | $0.5000 input | $1.50 output
TTM-R2 is IBM's larger-data continuation of the TinyTimeMixer line. IBM positions it as a better-performing follow-on to R1 while preserving the small, fast deployment profile that makes TinyTimeMixer practical on CPUs and lightweight hosted inference. It remains a focused family of context- and horizon-specific checkpoints rather than a single universal TSFM.
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 forecasting corpus built from Australian Electricity and Weather, Bitcoin, KDD Cup 2018, London Smart Meters, Saugeen River Flow, Solar, US Births, and wind datasets; IBM states R2 used about 700M 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