diff --git a/benchmarks/fev_bench/models.yaml b/benchmarks/fev_bench/models.yaml
index dc9ac07..22b76d3 100644
--- a/benchmarks/fev_bench/models.yaml
+++ b/benchmarks/fev_bench/models.yaml
@@ -307,3 +307,11 @@ TimeRSI:
   model_type: closed-api
   zero_shot: false
   commercial_use: false
+
+timersi-1_5:
+  organization: GaTech & SamayLabs
+  display_name: TimeRSI-1.5
+  url: https://github.com/haoxin1998/TimeRSI4FevBench/tree/main/TimeRSI-1.5
+  model_type: closed-api
+  zero_shot: false
+  commercial_use: false
diff --git a/benchmarks/fev_bench/results/timersi-1_5.csv b/benchmarks/fev_bench/results/timersi-1_5.csv
new file mode 100644
index 0000000..a27fef7
--- /dev/null
+++ b/benchmarks/fev_bench/results/timersi-1_5.csv
@@ -0,0 +1,101 @@
+model_name,dataset_path,dataset_config,horizon,initial_cutoff,min_context_length,max_context_length,seasonality,eval_metric,extra_metrics,quantile_levels,id_column,timestamp_column,target,generate_univariate_targets_from,known_dynamic_columns,past_dynamic_columns,static_columns,num_windows,window_step_size,task_name,test_error,training_time_s,inference_time_s,num_forecasts,dataset_fingerprint,trained_on_this_dataset,fev_version,model_class,model_kwargs,SQL,MASE,WAPE,WQL
+TimeRSI-1.5,autogluon/fev_datasets,proenfo_gfc17,168,-3360,1,,24,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,target,,['airtemperature'],[],[],20,168,proenfo_gfc17,0.3202921904181096,19390.68894517152,4633.0217075306655,160,eba07ba0bb45e5dc,False,0.11.0.dev0,timersi15,{},0.3202921904181096,0.4010931786398283,0.025325529087469906,0.02018896690740734
+TimeRSI-1.5,autogluon/fev_datasets,entsoe_15T,96,-1920,1,,96,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,target,,"['radiation_diffuse_horizontal', 'radiation_direct_horizontal', 'temperature']",[],[],20,96,entsoe_15T,0.37834020990976364,30452.39398156637,5716.881773153553,120,762c7ee326587aa2,False,0.11.0.dev0,timersi15,{},0.37834020990976364,0.4481250154260933,0.02874303140611124,0.025927736483345794
+TimeRSI-1.5,autogluon/fev_datasets,entsoe_30T,96,-1920,1,,48,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,target,,"['radiation_diffuse_horizontal', 'radiation_direct_horizontal', 'temperature']",[],[],20,96,entsoe_30T,0.356633082172445,26682.89868747699,5416.896027542371,120,0416fc7d5fcf96e2,False,0.11.0.dev0,timersi15,{},0.356633082172445,0.4352514644248874,0.028677748371028745,0.02398813678995257
+TimeRSI-1.5,autogluon/fev_datasets,epf_pjm,24,-480,1,,24,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,target,,"['System load forecast', 'Zonal COMED load foecast']",[],[],20,24,epf_pjm,0.35305935500983193,14370.733349290533,397.0667563970201,20,6752d1881d4327d6,False,0.11.0.dev0,timersi15,{},0.35305935500983193,0.43605524465404466,0.07517214778266891,0.06117811541073154
+TimeRSI-1.5,autogluon/fev_datasets,proenfo_gfc14,168,-3360,1,,24,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,target,,['airtemperature'],[],[],20,168,proenfo_gfc14,0.2570864356357347,18103.104361949612,4061.7861605000917,20,a2f90b2f1ba52e38,False,0.11.0.dev0,timersi15,{},0.2570864356357347,0.3247571420213419,0.015965728868575703,0.012640295488751865
+TimeRSI-1.5,autogluon/fev_datasets,entsoe_1H,168,-3360,1,,24,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,target,,"['radiation_diffuse_horizontal', 'radiation_direct_horizontal', 'temperature']",[],[],20,168,entsoe_1H,0.2767618064160948,25288.650277575074,4278.883882812193,120,aff93292e497726b,False,0.11.0.dev0,timersi15,{},0.2767618064160948,0.34583746813198973,0.020736051832719572,0.01641275469976195
+TimeRSI-1.5,autogluon/fev_datasets,solar_with_weather_1H,24,-480,1,,24,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,target,,"['day_length', 'humidity', 'pressure', 'rain_1h', 'snow_1h', 'temp', 'wind_speed']","['clouds_all', 'global_horizontal_irradiance']",[],20,24,solar_with_weather_1H,0.6465752411892355,39708.67353891955,5343.759841973446,20,4a140710760f779a,False,0.11.0.dev0,timersi15,{},0.6465752411892355,0.801573011792638,0.9343065154548222,0.8023715702604888
+TimeRSI-1.5,autogluon/fev_datasets,boomlet_1676,96,-1920,1,,48,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,"['target_0', 'target_1', 'target_10', 'target_11', 'target_12', 'target_13', 'target_14', 'target_15', 'target_16', 'target_17', 'target_18', 'target_19', 'target_2', 'target_20', 'target_21', 'target_22', 'target_23', 'target_24', 'target_25', 'target_26', 'target_27', 'target_28', 'target_29', 'target_3', 'target_30', 'target_31', 'target_32', 'target_33', 'target_34', 'target_35', 'target_36', 'target_37', 'target_38', 'target_39', 'target_4', 'target_40', 'target_41', 'target_42', 'target_43', 'target_44', 'target_45', 'target_46', 'target_47', 'target_48', 'target_49', 'target_5', 'target_50', 'target_51', 'target_52', 'target_53', 'target_54', 'target_55', 'target_56', 'target_57', 'target_58', 'target_59', 'target_6', 'target_60', 'target_61', 'target_62', 'target_63', 'target_64', 'target_65', 'target_66', 'target_67', 'target_68', 'target_69', 'target_7', 'target_70', 'target_71', 'target_72', 'target_73', 'target_74', 'target_75', 'target_76', 'target_77', 'target_78', 'target_79', 'target_8', 'target_80', 'target_81', 'target_82', 'target_83', 'target_84', 'target_85', 'target_86', 'target_87', 'target_88', 'target_89', 'target_9', 'target_90', 'target_91', 'target_92', 'target_93', 'target_94', 'target_95', 'target_96', 'target_97', 'target_98', 'target_99']",,[],[],[],20,96,boomlet_1676,0.5484100546033653,8660.847053473351,1958.6847267394796,2000,027ec0ef1e78a6f2,False,0.11.0.dev0,timersi15,{},0.5484100546033653,0.6828445952710991,0.31448188364421215,0.24724518245769378
+TimeRSI-1.5,autogluon/fev_datasets,epf_de,24,-480,1,,24,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,target,,"['Ampirion Load Forecast', 'PV+Wind Forecast']",[],[],20,24,epf_de,0.4701011146717164,46857.40318020006,4811.616543226462,20,ad020fd54ab7078f,False,0.11.0.dev0,timersi15,{},0.4701011146717164,0.5756063794626198,0.3623250261129474,0.30776576481554424
+TimeRSI-1.5,autogluon/fev_datasets,solar_with_weather_15T,96,-1920,1,,96,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,target,,"['day_length', 'humidity', 'pressure', 'rain_1h', 'snow_1h', 'temp', 'wind_speed']","['clouds_all', 'global_horizontal_irradiance']",[],20,96,solar_with_weather_15T,0.6029170826964341,46845.33496341426,5321.053449994838,20,52351e76b7090ab1,False,0.11.0.dev0,timersi15,{},0.6029170826964341,0.7769333611517112,0.9752702752293947,0.8097361134208864
+TimeRSI-1.5,autogluon/fev_datasets,boomlet_1631,96,-1920,1,,48,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,"['target_0', 'target_1', 'target_10', 'target_11', 'target_12', 'target_13', 'target_14', 'target_15', 'target_16', 'target_17', 'target_18', 'target_19', 'target_2', 'target_20', 'target_21', 'target_22', 'target_23', 'target_24', 'target_25', 'target_26', 'target_27', 'target_28', 'target_29', 'target_3', 'target_30', 'target_31', 'target_32', 'target_33', 'target_34', 'target_35', 'target_36', 'target_37', 'target_38', 'target_39', 'target_4', 'target_5', 'target_6', 'target_7', 'target_8', 'target_9']",,[],[],[],20,96,boomlet_1631,0.5687187330228701,7889.333062987626,1835.5464706455687,800,d69b69e987e32a2b,False,0.11.0.dev0,timersi15,{},0.5687187330228701,0.7129593161671495,0.3100488804598518,0.2467331531479639
+TimeRSI-1.5,autogluon/fev_datasets,boomlet_619,60,-1200,1,,1440,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,"['target_0', 'target_1', 'target_10', 'target_11', 'target_12', 'target_13', 'target_14', 'target_15', 'target_16', 'target_17', 'target_18', 'target_19', 'target_2', 'target_20', 'target_21', 'target_22', 'target_23', 'target_24', 'target_25', 'target_26', 'target_27', 'target_28', 'target_29', 'target_3', 'target_30', 'target_31', 'target_32', 'target_33', 'target_34', 'target_35', 'target_36', 'target_37', 'target_38', 'target_39', 'target_4', 'target_40', 'target_41', 'target_42', 'target_43', 'target_44', 'target_45', 'target_46', 'target_47', 'target_48', 'target_49', 'target_5', 'target_50', 'target_51', 'target_6', 'target_7', 'target_8', 'target_9']",,[],[],[],20,60,boomlet_619,0.28457842599550276,33750.213169245515,7762.036094031685,1040,a20d9d612ea2e091,False,0.11.0.dev0,timersi15,{},0.28457842599550276,0.3730277693780094,0.2514055807277098,0.19278543586907396
+TimeRSI-1.5,autogluon/fev_datasets,boomlet_285,60,-1200,1,,1440,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,"['target_0', 'target_1', 'target_10', 'target_11', 'target_12', 'target_13', 'target_14', 'target_15', 'target_16', 'target_17', 'target_18', 'target_19', 'target_2', 'target_20', 'target_21', 'target_22', 'target_23', 'target_24', 'target_25', 'target_26', 'target_27', 'target_28', 'target_29', 'target_3', 'target_30', 'target_31', 'target_32', 'target_33', 'target_34', 'target_35', 'target_36', 'target_37', 'target_38', 'target_39', 'target_4', 'target_40', 'target_41', 'target_42', 'target_43', 'target_44', 'target_45', 'target_46', 'target_47', 'target_48', 'target_49', 'target_5', 'target_50', 'target_51', 'target_52', 'target_53', 'target_54', 'target_55', 'target_56', 'target_57', 'target_58', 'target_59', 'target_6', 'target_60', 'target_61', 'target_62', 'target_63', 'target_64', 'target_65', 'target_66', 'target_67', 'target_68', 'target_69', 'target_7', 'target_70', 'target_71', 'target_72', 'target_73', 'target_74', 'target_8', 'target_9']",,[],[],[],20,60,boomlet_285,0.2599044016487284,34827.58303211662,6456.521511684451,1500,b08e8ba2a228e2e5,False,0.11.0.dev0,timersi15,{},0.2599044016487284,0.3322626096403745,0.15427377150999466,0.12603065513133171
+TimeRSI-1.5,autogluon/fev_datasets,hermes,52,-52,1,,1,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,target,,['external'],[],"['category', 'country']",1,52,hermes,0.5885780368882805,4529.602990960237,249.50377410114743,10000,107b852d349c8182,False,0.11.0.dev0,timersi15,{},0.5885780368882805,0.7520189050993195,0.002787102084889565,0.0021741109492715103
+TimeRSI-1.5,autogluon/fev_datasets,favorita_stores_1M,12,-24,1,,12,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,sales,,['onpromotion'],['oil_price'],"['city', 'cluster', 'family', 'state', 'store_nbr', 'type']",2,12,favorita_stores_1M,1.762572901285853,2650.7941095943097,437.335655340692,3158,84fb97f68dbadc4d,False,0.11.0.dev0,timersi15,{},1.762572901285853,1.9009741503543196,0.11311634799972464,0.10159791533747417
+TimeRSI-1.5,autogluon/fev_datasets,solar_1D,28,-280,1,,1,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,target,,[],[],[],10,28,solar_1D,0.6028815912290391,2623.912543219514,668.3954885380421,1370,61a16072f577b902,False,0.11.0.dev0,timersi15,{},0.6028815912290391,0.7837432661517788,0.24615135465805085,0.1887570950073477
+TimeRSI-1.5,autogluon/fev_datasets,epf_np,24,-480,1,,24,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,target,,"['Grid load forecast', 'Wind power forecast']",[],[],20,24,epf_np,0.5301495557265433,4870.474378977902,522.5220962361034,20,0a17a2edca8b0670,False,0.11.0.dev0,timersi15,{},0.5301495557265433,0.6902619243361046,0.0311883523505461,0.023995949730156153
+TimeRSI-1.5,autogluon/fev_datasets,boomlet_1209,288,-5760,1,,288,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,"['target_0', 'target_1', 'target_10', 'target_11', 'target_12', 'target_13', 'target_14', 'target_15', 'target_16', 'target_17', 'target_18', 'target_19', 'target_2', 'target_20', 'target_21', 'target_22', 'target_23', 'target_24', 'target_25', 'target_26', 'target_27', 'target_28', 'target_29', 'target_3', 'target_30', 'target_31', 'target_32', 'target_33', 'target_34', 'target_35', 'target_36', 'target_37', 'target_38', 'target_39', 'target_4', 'target_40', 'target_41', 'target_42', 'target_43', 'target_44', 'target_45', 'target_46', 'target_47', 'target_48', 'target_49', 'target_5', 'target_50', 'target_51', 'target_52', 'target_6', 'target_7', 'target_8', 'target_9']",,[],[],[],20,288,boomlet_1209,0.6324751125775868,8369.96639671325,2692.900146572408,1060,af76fff1b484ede3,False,0.11.0.dev0,timersi15,{},0.6324751125775868,0.7416596196002792,0.28368563382347,0.24001357018324626
+TimeRSI-1.5,autogluon/fev_datasets,favorita_stores_1D,28,-280,1,,7,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,sales,,"['holiday', 'onpromotion']",['oil_price'],"['city', 'cluster', 'family', 'state', 'store_nbr', 'type']",10,28,favorita_stores_1D,0.9095043728148277,16814.155835785197,3117.9340287160885,15790,19461c7044524e5b,False,0.11.0.dev0,timersi15,{},0.9095043728148277,1.1333992089844247,0.14006795969126726,0.11140914538287952
+TimeRSI-1.5,autogluon/fev_datasets,proenfo_gfc12,168,-1680,1,,24,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,target,,['airtemperature'],[],[],10,168,proenfo_gfc12,0.4219662978328812,30624.49048803585,2170.6376046176356,110,b9d66f77d6db1337,False,0.11.0.dev0,timersi15,{},0.4219662978328812,0.5147619022641896,0.04374462631420178,0.03518397564527963
+TimeRSI-1.5,autogluon/fev_datasets,boomlet_1282,60,-1200,1,,1440,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,"['target_0', 'target_1', 'target_10', 'target_11', 'target_12', 'target_13', 'target_14', 'target_15', 'target_16', 'target_17', 'target_18', 'target_19', 'target_2', 'target_20', 'target_21', 'target_22', 'target_23', 'target_24', 'target_25', 'target_26', 'target_27', 'target_28', 'target_29', 'target_3', 'target_30', 'target_31', 'target_32', 'target_33', 'target_34', 'target_4', 'target_5', 'target_6', 'target_7', 'target_8', 'target_9']",,[],[],[],20,60,boomlet_1282,0.39031390588434467,7036.560525573803,2178.4198805603664,700,c0f21ca23524dd1f,False,0.11.0.dev0,timersi15,{},0.39031390588434467,0.4761279852230144,0.32918973330511736,0.2673058431075714
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+TimeRSI-1.5,autogluon/fev_datasets,rossmann_1W,13,-104,1,,1,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,Sales,,"['Open', 'Promo', 'SchoolHoliday', 'StateHoliday']",['Customers'],"['Assortment', 'CompetitionDistance', 'CompetitionOpenSinceMonth', 'CompetitionOpenSinceYear', 'Promo2', 'Promo2SinceWeek', 'Promo2SinceYear', 'PromoInterval', 'Store', 'StoreType']",8,13,rossmann_1W,0.24069953892936527,7131.274977848201,2527.1060965796933,8920,e18c12f0c75cf8c0,False,0.11.0.dev0,timersi15,{},0.24069953892936527,0.27995161327333773,0.07250664939902057,0.062423892915394456
+TimeRSI-1.5,autogluon/fev_datasets,hierarchical_sales_1D,28,-280,1,,7,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,target,,[],[],[],10,28,hierarchical_sales_1D,0.5443060286956689,62622.12275847996,9886.125381967371,1180,77b3d008284e117b,False,0.11.0.dev0,timersi15,{},0.5443060286956689,0.6776657787766455,0.6862879844433707,0.5561770234786818
+TimeRSI-1.5,autogluon/fev_datasets,hierarchical_sales_1W,13,-130,1,,1,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,target,,[],[],[],10,13,hierarchical_sales_1W,0.6152958420849479,6243.834834948831,1932.428128415698,1180,2b2b335c105dabf3,False,0.11.0.dev0,timersi15,{},0.6152958420849479,0.7503147786532337,0.4265676396060063,0.3623651876221671
+TimeRSI-1.5,autogluon/fev_datasets,us_consumption_1Q,8,-80,1,,4,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,target,,[],[],[],10,8,us_consumption_1Q,1.62311446442173,8265.014794472445,2464.521660311846,310,9a76cd11c4c2c07e,False,0.11.0.dev0,timersi15,{},1.62311446442173,2.0025529808820215,0.030303260315087475,0.02491487757093283
+TimeRSI-1.5,autogluon/fev_datasets,uci_air_quality_1D,28,-308,1,,7,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,"['C6H6(GT)', 'CO(GT)', 'NO2(GT)', 'NOx(GT)']",,"['AH', 'RH', 'T']",[],[],11,28,uci_air_quality_1D,1.045852550179693,6670.593392847134,2257.4585809149025,44,0d2ba39e4e4ce5f4,False,0.11.0.dev0,timersi15,{},1.045852550179693,1.3136281279572293,0.2723299003903959,0.2153591213846915
+TimeRSI-1.5,autogluon/fev_datasets,world_co2_emissions,5,-45,1,,1,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,target,,[],[],[],9,5,world_co2_emissions,2.5758539872663864,8011.769341375943,2132.14844792803,1719,c78d3682201594d9,False,0.11.0.dev0,timersi15,{},2.5758539872663864,3.139945563047307,0.08071804093816307,0.06607628115727567
+TimeRSI-1.5,autogluon/fev_datasets,restaurant,28,-224,1,,7,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,target,,[],[],"['air_area_name', 'air_genre_name', 'latitude', 'longitude']",8,28,restaurant,0.679942192626756,8184.624082233938,2102.1347017614794,6502,5af240c09db342cf,False,0.11.0.dev0,timersi15,{},0.679942192626756,0.843050080030452,0.35346285080412587,0.27879783411153436
+TimeRSI-1.5,autogluon/fev_datasets,SZ_TAXI_15T,96,-960,1,,96,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,target,,[],[],[],10,96,SZ_TAXI_15T,0.39101235295282233,7483.165343608632,2691.85559238707,1560,947f77f0c19ac7ce,False,0.11.0.dev0,timersi15,{},0.39101235295282233,0.4979040424326813,0.2382314354203861,0.18680898779562635
+TimeRSI-1.5,autogluon/fev_datasets,us_consumption_1Y,5,-50,1,,1,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,target,,[],[],[],10,5,us_consumption_1Y,3.239108780696495,7871.726992609639,2947.851413613224,310,d29d0d81db6393b4,False,0.11.0.dev0,timersi15,{},3.239108780696495,3.9832464697583396,0.05084500933840014,0.03980934298765512
+TimeRSI-1.5,autogluon/fev_datasets,redset_1H,24,-240,1,,24,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,target,,[],[],['subset'],10,24,redset_1H,1.2414764224661905,19019.7887867476,2064.8478650131665,1380,f7cbb47cb5f76ea7,False,0.11.0.dev0,timersi15,{},1.2414764224661905,1.3481797215001066,0.20828363782307519,0.16980986473847065
+TimeRSI-1.5,autogluon/fev_datasets,hospital_admissions_1D,28,-560,1,,7,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,target,,[],[],[],20,28,hospital_admissions_1D,0.5541943590892442,9504.687760106039,4504.266296653053,160,2a4e1183560f9bb2,False,0.11.0.dev0,timersi15,{},0.5541943590892442,0.7189868084743594,0.5333049205646077,0.41106216104781634
+TimeRSI-1.5,autogluon/fev_datasets,us_consumption_1M,12,-120,1,,12,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,target,,[],[],[],10,12,us_consumption_1M,1.443220719921627,6433.263570567776,1894.749795706202,310,c882f886bec32c78,False,0.11.0.dev0,timersi15,{},1.443220719921627,1.7539599452558192,0.022964360679926483,0.020032618117348362
+TimeRSI-1.5,autogluon/fev_datasets,gvar,8,-80,1,,4,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,"['Dp', 'ep', 'eq', 'lr', 'r', 'y']",,[],"['pmat', 'pmetal', 'poil']",[],10,8,gvar,0.5418152987648528,12791.614621333696,2779.0051714184497,1980,61766544be22840b,False,0.11.0.dev0,timersi15,{},0.5418152987648528,0.6583351409090592,0.017385441105632886,0.014204746368369311
+TimeRSI-1.5,autogluon/fev_datasets,rohlik_sales_1W,8,2023-12-15T00:00:00,8,,1,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,sales,,"['holiday', 'school_holidays', 'sell_price_main', 'shops_closed', 'total_orders', 'type_0_discount', 'type_1_discount', 'type_2_discount', 'type_3_discount', 'type_4_discount', 'type_5_discount', 'type_6_discount', 'winter_school_holidays']",['availability'],"['L1_category_name_en', 'L2_category_name_en', 'L3_category_name_en', 'L4_category_name_en', 'name', 'product_unique_id', 'warehouse']",1,8,rohlik_sales_1W,1.0740508430922584,12237.159898780294,506.19878884847276,3942,a1817f8223c08fb5,False,0.11.0.dev0,timersi15,{},1.0740508430922584,1.2646296528916217,0.1862015887036032,0.15626332518306396
+TimeRSI-1.5,autogluon/fev_datasets,rohlik_orders_1D,61,2023-05-01T00:00:00,1,,7,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,orders,,"['holiday', 'school_holidays', 'shops_closed', 'winter_school_holidays']","['blackout', 'frankfurt_shutdown', 'mini_shutdown', 'mov_change', 'precipitation', 'shutdown', 'snow', 'user_activity_1', 'user_activity_2']",[],5,61,rohlik_orders_1D,0.8874709177815063,5624.113584492123,1318.2233132094261,35,743d7d85eea679ed,False,0.11.0.dev0,timersi15,{},0.8874709177815063,1.0700355632561995,0.05081319609539294,0.041867725469196905
+TimeRSI-1.5,autogluon/fev_datasets,kdd_cup_2022_1D,14,-140,1,,1,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,Patv,,[],"['Etmp', 'Itmp', 'Ndir', 'Pab1', 'Pab2', 'Pab3', 'Prtv', 'Wdir', 'Wspd']",[],10,14,kdd_cup_2022_1D,0.6944790288080547,7390.304369289007,3735.488765713361,1340,53e3bfa3689aa2d7,False,0.11.0.dev0,timersi15,{},0.6944790288080547,0.8997349194711735,0.7192092894953769,0.5534428186723945
+TimeRSI-1.5,autogluon/fev_datasets,m5_1D,28,-28,1,,7,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,target,,"['event_Cultural', 'event_National', 'event_Religious', 'event_Sporting', 'sell_price', 'snap_CA', 'snap_TX', 'snap_WI']",[],"['cat_id', 'dept_id', 'item_id', 'state_id', 'store_id']",1,28,m5_1D,0.704071380498631,13712.162947779754,520.4444836014882,30490,a5408e93540ec5c9,False,0.11.0.dev0,timersi15,{},0.704071380498631,0.8678020156307173,0.6951364587879759,0.5438063305883428
+TimeRSI-1.5,autogluon/fev_datasets,m5_1W,13,-13,1,,1,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,target,,"['event_Cultural', 'event_National', 'event_Religious', 'event_Sporting', 'sell_price', 'snap_CA', 'snap_TX', 'snap_WI']",[],"['cat_id', 'dept_id', 'item_id', 'state_id', 'store_id']",1,13,m5_1W,0.8949196569569957,12845.463048883481,642.0591916667763,30490,0c7d59ea6d50dbdf,False,0.11.0.dev0,timersi15,{},0.8949196569569957,1.1085165756597406,0.41468158512416764,0.3319533029790754
+TimeRSI-1.5,autogluon/fev_datasets,rohlik_orders_1W,8,2023-05-01T00:00:00,1,,1,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,orders,,"['holiday', 'school_holidays', 'shops_closed', 'winter_school_holidays']","['blackout', 'frankfurt_shutdown', 'mini_shutdown', 'mov_change', 'precipitation', 'shutdown', 'snow', 'user_activity_1', 'user_activity_2']",[],5,8,rohlik_orders_1W,1.307086389465971,4353.011892348324,1538.8454261149745,35,18a03d658590ecd3,False,0.11.0.dev0,timersi15,{},1.307086389465971,1.6074395734536107,0.05266858071495304,0.04284037090788393
+TimeRSI-1.5,autogluon/fev_datasets,m5_1M,12,-12,6,,12,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,target,,"['event_Cultural', 'event_National', 'event_Religious', 'event_Sporting', 'sell_price', 'snap_CA', 'snap_TX', 'snap_WI']",[],"['cat_id', 'dept_id', 'item_id', 'state_id', 'store_id']",1,12,m5_1M,0.9413045472664149,7642.804350730032,303.61768913059495,29364,b562dee8546ce598,False,0.11.0.dev0,timersi15,{},0.9413045472664149,1.1320482781234262,0.4144774432231611,0.3293386130634416
+TimeRSI-1.5,autogluon/fev_datasets,uk_covid_nation_1W,8,-32,1,,1,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,"['cumulative_admissions', 'cumulative_cases', 'cumulative_deaths']",,[],"['cumulative_vaccinated_1', 'cumulative_vaccinated_2', 'cumulative_vaccinated_3', 'hospital_cases', 'icu_ventilator_occupancy']",[],4,8,uk_covid_nation_1W/cumulative,2.724631413514369,4529.127776046109,1181.8102989670604,48,a1bd24bd7d949574,False,0.11.0.dev0,timersi15,{},2.724631413514369,3.5272440094551465,0.03397826696847056,0.025927782931923868
+TimeRSI-1.5,autogluon/fev_datasets,ETT_1W,13,-65,1,,1,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,"['HUFL', 'HULL', 'LUFL', 'LULL', 'MUFL', 'MULL', 'OT']",,[],[],[],5,13,ETT_1W,2.229920405192691,4755.339640542343,1334.538697037613,70,2e18066fd2e18f63,False,0.11.0.dev0,timersi15,{},2.229920405192691,2.5659403144748767,0.4678690899468715,0.3746517517643174
+TimeRSI-1.5,autogluon/fev_datasets,uk_covid_nation_1W,8,-32,1,,1,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,"['new_admissions', 'new_cases', 'new_deaths']",,[],"['hospital_cases', 'icu_ventilator_occupancy', 'new_vaccinated_1', 'new_vaccinated_2', 'new_vaccinated_3']",[],4,8,uk_covid_nation_1W/new,4.960767035694488,4567.145748905488,998.5144251200836,48,a1bd24bd7d949574,False,0.11.0.dev0,timersi15,{},4.960767035694488,6.197116563849284,0.7555539859243654,0.5997175361803094
+TimeRSI-1.5,autogluon/fev_datasets,rohlik_sales_1D,14,2023-12-15T00:00:00,14,,7,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,sales,,"['holiday', 'school_holidays', 'sell_price_main', 'shops_closed', 'total_orders', 'type_0_discount', 'type_1_discount', 'type_2_discount', 'type_3_discount', 'type_4_discount', 'type_5_discount', 'type_6_discount', 'winter_school_holidays']",['availability'],"['L1_category_name_en', 'L2_category_name_en', 'L3_category_name_en', 'L4_category_name_en', 'name', 'product_unique_id', 'warehouse']",1,14,rohlik_sales_1D,0.8680560997162753,12242.775168668944,174.00000734487548,4116,bdd7a282f9fc98e5,False,0.11.0.dev0,timersi15,{},0.8680560997162753,1.075470944489446,0.26985320226409454,0.2186267344417273
+TimeRSI-1.5,autogluon/fev_datasets,walmart,39,-39,1,,1,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,target,,"['CPI', 'Fuel_Price', 'IsHoliday', 'MarkDown1', 'MarkDown2', 'MarkDown3', 'MarkDown4', 'MarkDown5', 'Temperature', 'Unemployment']",[],"['Dept', 'Size', 'Store', 'Type']",1,39,walmart,0.6491477057764946,2280.8691712133586,274.6089513564948,2936,84f95b6543281d0d,False,0.11.0.dev0,timersi15,{},0.6491477057764946,0.844816649297503,0.0976453796871347,0.07314735684382409
+TimeRSI-1.5,autogluon/fev_datasets,solar_1W,13,-13,1,,1,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,target,,[],[],[],1,13,solar_1W,0.7662307604218397,1487.7608701691497,211.89957616454922,137,b957c1ccfd8bdefc,False,0.11.0.dev0,timersi15,{},0.7662307604218397,0.8909846773512325,0.15014292384964473,0.12967026932252596
+TimeRSI-1.5,autogluon/fev_datasets,SZ_TAXI_1H,168,-336,1,,24,SQL,"['MASE', {'name': 'WAPE', 'epsilon': 1.0}, {'name': 'WQL', 'epsilon': 1.0}]","[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]",id,timestamp,target,,[],[],[],2,168,SZ_TAXI_1H,0.3989174387003167,1618.225831811782,549.3199733586516,312,c8fc2c774fa27320,False,0.11.0.dev0,timersi15,{},0.3989174387003167,0.4931716813748127,0.1647024187896306,0.13377910628651185
diff --git a/models/timersi15/model.py b/models/timersi15/model.py
new file mode 100644
index 0000000..f1c742c
--- /dev/null
+++ b/models/timersi15/model.py
@@ -0,0 +1,22 @@
+"""FEV interface for the standalone TimeRSI-1.5 implementation."""
+from fev.model import ForecastingModel
+from timersi15.runtime import Config, fit_predict
+
+
+class TimeRSI15Model(ForecastingModel):
+    model_name = "timersi15"
+    trained_on_datasets = []
+
+    def __init__(self, checkpoint_path="mistralai/Timestral-209M", device="cuda:0",
+                 run_root="timersi15-runs", regenerate_decisions=False,
+                 agent_model="claude-opus-5", effort="high", vertex_project=None, artifacts_dir=None):
+        super().__init__()
+        self.config = Config(checkpoint_path=checkpoint_path, device=device,
+            run_root=run_root, regenerate_decisions=regenerate_decisions,
+            agent_model=agent_model, effort=effort, vertex_project=vertex_project, artifacts_dir=artifacts_dir)
+
+    def _fit_predict(self, task):
+        forecasts, timing = fit_predict(task, self.config)
+        self.training_time = timing["training_time_s"]
+        self.inference_time = timing["inference_time_s"]
+        return forecasts
diff --git a/models/timersi15/requirements.txt b/models/timersi15/requirements.txt
new file mode 100644
index 0000000..194857e
--- /dev/null
+++ b/models/timersi15/requirements.txt
@@ -0,0 +1 @@
+timersi-fevbench15 @ https://github.com/haoxin1998/TimeRSI4FevBench/archive/a8d036bf7bafadc31142560fd45f56de121b876b.tar.gz#subdirectory=TimeRSI-1.5