diff --git a/.buildkite/test-pipeline.yaml b/.buildkite/test-pipeline.yaml
index 80a5a610c8ac9..4e7bea25e1717 100644
--- a/.buildkite/test-pipeline.yaml
+++ b/.buildkite/test-pipeline.yaml
@@ -274,17 +274,6 @@ steps:
     - pytest -v -s samplers
     - VLLM_USE_FLASHINFER_SAMPLER=1 pytest -v -s samplers
 
-- label: LogitsProcessor Test # 5min
-  mirror_hardwares: [amdexperimental, amdproduction]
-  source_file_dependencies:
-  - vllm/model_executor/layers
-  - vllm/model_executor/guided_decoding
-  - tests/test_logits_processor
-  - tests/model_executor/test_guided_processors
-  commands:
-    - pytest -v -s test_logits_processor.py
-    - pytest -v -s model_executor/test_guided_processors.py
-
 - label: Speculative decoding tests # 40min
   mirror_hardwares: [amdexperimental]
   source_file_dependencies:
@@ -397,6 +386,17 @@ steps:
     - pytest -v -s tensorizer_loader
     - pytest -v -s entrypoints/openai/test_tensorizer_entrypoint.py
 
+- label: Model Executor Test
+  mirror_hardwares: [amdexperimental, amdproduction]
+  soft_fail: true
+  source_file_dependencies:
+  - vllm/model_executor
+  - tests/model_executor
+  commands:
+    - apt-get update && apt-get install -y curl libsodium23
+    - export VLLM_WORKER_MULTIPROC_METHOD=spawn
+    - pytest -v -s model_executor
+
 - label: Benchmarks # 9min
   mirror_hardwares: [amdexperimental, amdproduction]
   working_dir: "/vllm-workspace/.buildkite"
diff --git a/tests/test_logits_processor.py b/tests/model_executor/test_logits_processor.py
similarity index 100%
rename from tests/test_logits_processor.py
rename to tests/model_executor/test_logits_processor.py
diff --git a/tests/model_executor/test_model_load_with_params.py b/tests/model_executor/test_model_load_with_params.py
index f8efa2eff857b..7fda1f0e80d07 100644
--- a/tests/model_executor/test_model_load_with_params.py
+++ b/tests/model_executor/test_model_load_with_params.py
@@ -4,7 +4,7 @@ import os
 
 import pytest
 
-from vllm.model_executor.layers.pooler import CLSPool, PoolingType
+from vllm.model_executor.layers.pooler import CLSPool, MeanPool, PoolingType
 from vllm.model_executor.models.bert import BertEmbeddingModel
 from vllm.model_executor.models.roberta import RobertaEmbeddingModel
 from vllm.platforms import current_platform
@@ -14,7 +14,7 @@ MODEL_NAME = os.environ.get("MODEL_NAME", "BAAI/bge-base-en-v1.5")
 REVISION = os.environ.get("REVISION", "main")
 
 MODEL_NAME_ROBERTA = os.environ.get("MODEL_NAME",
-                                    "intfloat/multilingual-e5-small")
+                                    "intfloat/multilingual-e5-base")
 REVISION_ROBERTA = os.environ.get("REVISION", "main")
 
 
@@ -40,17 +40,15 @@ def test_model_loading_with_params(vllm_runner):
 
         # asserts on the pooling config files
         assert model_config.pooler_config.pooling_type == PoolingType.CLS.name
-        assert model_config.pooler_config.pooling_norm
+        assert model_config.pooler_config.normalize
 
         # asserts on the tokenizer loaded
         assert model_tokenizer.tokenizer_id == "BAAI/bge-base-en-v1.5"
-        assert model_tokenizer.tokenizer_config["do_lower_case"]
         assert model_tokenizer.tokenizer.model_max_length == 512
 
         def check_model(model):
             assert isinstance(model, BertEmbeddingModel)
-            assert model._pooler.pooling_type == PoolingType.CLS
-            assert model._pooler.normalize
+            assert isinstance(model._pooler, CLSPool)
 
         vllm_model.apply_model(check_model)
 
@@ -80,16 +78,15 @@ def test_roberta_model_loading_with_params(vllm_runner):
 
         # asserts on the pooling config files
         assert model_config.pooler_config.pooling_type == PoolingType.MEAN.name
-        assert model_config.pooler_config.pooling_norm
+        assert model_config.pooler_config.normalize
 
         # asserts on the tokenizer loaded
-        assert model_tokenizer.tokenizer_id == "intfloat/multilingual-e5-small"
-        assert not model_tokenizer.tokenizer_config["do_lower_case"]
+        assert model_tokenizer.tokenizer_id == "intfloat/multilingual-e5-base"
+        assert model_tokenizer.tokenizer.model_max_length == 512
 
         def check_model(model):
             assert isinstance(model, RobertaEmbeddingModel)
-            assert model._pooler.pooling_type == PoolingType.MEAN
-            assert model._pooler.normalize
+            assert isinstance(model._pooler, MeanPool)
 
         vllm_model.apply_model(check_model)
 
diff --git a/tests/model_executor/weight_utils.py b/tests/model_executor/test_weight_utils.py
similarity index 100%
rename from tests/model_executor/weight_utils.py
rename to tests/model_executor/test_weight_utils.py