Sunday, October 25, 2026
Tech Beat
Sep 9, 2026, 3:36 PMArtificial Intelligence

IBM Granite PatchTST-FM-r2 Leads Commercially Licensed Zero-Shot Forecasting Models

IBM's 385M-parameter Granite PatchTST-FM-r2 ranks first among permissively licensed zero-shot models, adding probabilistic forecasts and data imputation.

Listen to this briefingAudio briefing

Summary

IBM released Granite Time Series PatchTST-FM-r2 on September 9, 2026, offering its weights, architecture, inference pipeline and reproducibility code through Hugging Face and Granite-TSFM. As of September 8, it ranked second among replicable, leakage-free zero-shot models on GIFT-Eval for CRPS and MASE, behind TimesFM-3, but first among models with permissive commercial licensing. Its geometric-mean CRPS was 0.467 and MASE was 0.6846. Against replicable models allowed to train on benchmark data, it placed third for CRPS and fourth for MASE, outperforming Chronos-2, Timer-S1 and Toto variants.

The roughly 385 million-parameter model handles contexts up to 8,192 steps, flexible forecast lengths, missing-value imputation and point or probabilistic forecasts through a 99-quantile head. Compared with PatchTST-FM-r1, IBM replaced transformer layers with conformer blocks combining self-attention, temporal convolution and two half-step feed-forward layers, expanded from 20 to 30 blocks, and added normalization, alternating convolution kernels of 3 and 5, plus 50% overlapping Hamming-weighted patches. Pretraining combines four documented sources, including selected GiftEvalPretrain data, modified KernelSynth data, GIFT-Eval-excluded TSMixup data and about 500,000 synthetic CauKer sequences of length 4,096. Users can choose Apache 2.0 or OpenMDW 1.0. Separately, Confluent Cloud Early Access supports PatchTST-FM-r1, FlowState-r1.1, TTM-r3 and TSPulse for live forecasting and anomaly detection through Apache Flink, but does not yet list r2.

Positives

  • PatchTST-FM-r2 ranks first among permissively licensed, replicable zero-shot models on GIFT-Eval and second overall for both CRPS and MASE.
  • A 0.467 geometric-mean CRPS and 0.6846 MASE place IBM immediately behind TimesFM-3 in leakage-free zero-shot testing.
  • The 99-quantile head supplies point forecasts, probability distributions and uncertainty intervals without task-specific fitting or fine-tuning.
  • Apache 2.0 and OpenMDW 1.0 licensing permits broad commercial use, modification and distribution.
  • Open weights, architecture, inference code and benchmark reproduction materials improve technical and governance transparency.
  • Contexts up to 8,192 steps, missing-value imputation and flexible forecast lengths broaden applications across demand, energy, traffic, prices and telemetry.

Risks & concerns

  • TimesFM-3 still leads PatchTST-FM-r2 in the replicable, leakage-free zero-shot GIFT-Eval comparison.
  • Including models allowed to use benchmark training data drops IBM to third for CRPS and fourth for MASE.
  • IBM says documented training data does not replace customers’ own model-governance and licensing reviews.
  • Confluent Cloud’s Early Access portfolio lists PatchTST-FM-r1, FlowState-r1.1, TTM-r3 and TSPulse, not the new r2 model.
Primary sourceHugging Face - Bloghttps://huggingface.co/blog/ibm-research/ibm-releases-sota-granite-time-series
Read full article
Editorial note: Tech Beat summarizes and analyzes third-party reporting. The source link is the authoritative article. This page does not reproduce the full source text.

More From The Wire

Artificial IntelligenceOct 24

AI Graveyard Grows as Character.ai, Relay and Major Products Fail

Artificial IntelligenceOct 24

Block Unveils Dessa, a Lifelike Voice AI That Runs Locally

Artificial IntelligenceOct 24

24 AI Agents You Can Text for Work, Travel and Family Tasks