5-Lens Empirical Quadrants & Non-Dominated Pareto Frontier
All 17 Facets (13) agent_development_orchestration ai_security_and_guardrails automation_ipaas_dag_durable embeddings_and_rerankers evaluation_and_regression_testing llm_frontier_cloud llm_open_weights_cloud memory_behavior_policies multimodal_vision_audio_3d observability_tracing_monitoring programmatic_prompt_workflow_optimization protocols_mcp_and_a2a rag_context_pipeline slm_cpu_edge_quantized team_simulation_provenance timeseries_foundation_models vector_and_transactional_storage
| Component | Facet | Quadrant & Frontier | Lens Scores | Cliff & WAR |
|---|---|---|---|---|
| Amazon Chronos-2 Covariate AWS / Amazon Science |
timeseries_foundation_models |
EMPIRICAL_LEADER PARETO | Exec: 96 · Fit: 93 · Wave: 94.08 | Cliff: 89% · WAR: +0.3 |
| Amazon Chronos-Bolt (Base) AWS / Amazon Science |
timeseries_foundation_models |
EMPIRICAL_LEADER PARETO | Exec: 97 · Fit: 94 · Wave: 94 | Cliff: 89% · WAR: +0.31 |
| Nixtla StatsForecast (AutoARIMA/AutoETS) Nixtla |
timeseries_foundation_models |
EMPIRICAL_LEADER PARETO | Exec: 99 · Fit: 95 · Wave: 93.32 | Cliff: 95% · WAR: +0.26 |
| Google TimesFM 2.0 (500M) Google Research |
timeseries_foundation_models |
EMPIRICAL_LEADER | Exec: 95 · Fit: 92 · Wave: 93.3 | Cliff: 86% · WAR: +0.29 |
| Datadog Toto (Open Weights) Datadog |
timeseries_foundation_models |
EMPIRICAL_LEADER | Exec: 94 · Fit: 93 · Wave: 92.96 | Cliff: 89% · WAR: +0.27 |
| Amazon Chronos-Bolt (Tiny CPU) AWS / Amazon Science |
timeseries_foundation_models |
EMPIRICAL_LEADER PARETO | Exec: 98 · Fit: 94 · Wave: 92.32 | Cliff: 89% · WAR: +0.27 |
| Salesforce Moirai-MoE Salesforce AI Research |
timeseries_foundation_models |
EMPIRICAL_LEADER | Exec: 92 · Fit: 91 · Wave: 91.62 | Cliff: 86% · WAR: +0.25 |
| PatchTST IBM / Princeton |
timeseries_foundation_models |
EMPIRICAL_LEADER | Exec: 96 · Fit: 93 · Wave: 90.84 | Cliff: 87% · WAR: +0.2 |
| MOMENT-1-Large CMU AutonLab |
timeseries_foundation_models |
EMPIRICAL_LEADER | Exec: 92 · Fit: 91 · Wave: 90.66 | Cliff: 86% · WAR: +0.22 |
| Sundial Time-Series Flow THUML |
timeseries_foundation_models |
EMPIRICAL_LEADER | Exec: 89 · Fit: 90 · Wave: 90.22 | Cliff: 84% · WAR: +0.23 |
| Timer-XL THUML |
timeseries_foundation_models |
EMPIRICAL_LEADER | Exec: 90 · Fit: 90 · Wave: 90.14 | Cliff: 84% · WAR: +0.21 |
| Lag-Llama Morgan Stanley / ServiceNow |
timeseries_foundation_models |
OPERATIONAL_WORKHORSE | Exec: 88 · Fit: 81 · Wave: 87.02 | Cliff: 80% · WAR: +0.16 |
| Nixtla TimeGPT-1 Nixtla |
timeseries_foundation_models |
EMPIRICAL_LEADER | Exec: 91 · Fit: 83 · Wave: 85.11 | Cliff: 86% · WAR: +0.21 |