diff --git a/ods_ci/tests/Tests/400__ods_dashboard/420__model_serving/LLMs/422__model_serving_llm_tgis_object_storages.robot b/ods_ci/tests/Tests/400__ods_dashboard/420__model_serving/LLMs/422__model_serving_llm_tgis_object_storages.robot
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+*** Settings ***
+Documentation     Collection of CLI tests to validate the model serving stack for Large Language Models (LLM).
+...               These tests leverage on TGIS Standalone Serving Runtime
+Resource          ../../../../Resources/OCP.resource
+Resource          ../../../../Resources/CLI/ModelServing/llm.resource
+Resource          ../../../../Resources/CLI/Minio.resource
+Library           OpenShiftLibrary
+Suite Setup       Suite Setup
+Suite Teardown    RHOSi Teardown
+Test Tags         KServe
+
+
+*** Variables ***
+${MODEL_S3_DIR}=    flan-t5-small-hf
+${TEST_NS}=    tgis-storages
+${TGIS_RUNTIME_NAME}=    tgis-runtime
+@{SEARCH_METRICS}=    tgi_    istio_
+
+  
+*** Test Cases ***
+Verify User Can Serve And Query A Model From Minio
+    [Documentation]    Basic tests for preparing, deploying and querying a LLM model
+    ...                using Kserve and Caikit+TGIS runtime
+    [Tags]    Tier1    RHOAIENG-3490
+    ${minio_namespace}=    Set Variable    minio-models
+    Deploy MinIO    namespace=${minio_namespace}
+    Wait For Pods To Be Ready    label_selector=app=minio
+    ...    namespace=${minio_namespace}
+    ${key}    ${pw}=    Get Minio Credentials    namespace=${minio_namespace}
+    Set Project And Runtime    runtime=${TGIS_RUNTIME_NAME}     namespace=${TEST_NS}-minio
+    ...    access_key_id=${key}    access_key=${pw}
+    ...    endpoint=minio-service.${minio_namespace}.svc.cluster.local:9000
+    ...    verify_ssl=${FALSE}    # temporary
+    ${test_namespace}=    Set Variable     ${TEST_NS}-minio
+    ${model_name}=    Set Variable    flan-t5-small-hf
+    ${models_names}=    Create List    ${model_name}
+    ${storage_uri}=    Set Variable    s3://models/${MODEL_S3_DIR}/
+    Compile Inference Service YAML    isvc_name=${model_name}
+    ...    sa_name=${DEFAULT_BUCKET_SA_NAME}
+    ...    model_storage_uri=${storage_uri}
+    ...    model_format=pytorch    serving_runtime=${TGIS_RUNTIME_NAME}
+    Deploy Model Via CLI    isvc_filepath=${INFERENCESERVICE_FILLED_FILEPATH}
+    ...    namespace=${test_namespace}
+    Wait For Pods To Be Ready    label_selector=serving.kserve.io/inferenceservice=${model_name}
+    ...    namespace=${test_namespace}
+    Query Model Multiple Times    model_name=${model_name}    runtime=${TGIS_RUNTIME_NAME}
+    ...    inference_type=all-tokens    n_times=1
+    ...    namespace=${test_namespace}
+    # Query Model Multiple Times    model_name=${model_name}    runtime=${TGIS_RUNTIME_NAME}
+    # ...    inference_type=streaming    n_times=1
+    # ...    namespace=${test_namespace}    validate_response=${FALSE}
+    # [Teardown]    Clean Up Test Project    test_ns=${test_namespace}
+    # ...    isvc_names=${models_names}    wait_prj_deletion=${FALSE}
+
+
+*** Keywords ***
+Suite Setup
+    [Documentation]
+    Skip If Component Is Not Enabled    kserve
+    # RHOSi Setup
+    Load Expected Responses
+    Run    git clone https://github.com/IBM/text-generation-inference/
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