diff --git a/tests/benchmarks/model_benchmarks/test_pytorch_mixtral.py b/tests/benchmarks/model_benchmarks/test_pytorch_mixtral.py
index ce0a1e3b8..db3bbbae9 100644
--- a/tests/benchmarks/model_benchmarks/test_pytorch_mixtral.py
+++ b/tests/benchmarks/model_benchmarks/test_pytorch_mixtral.py
@@ -15,14 +15,14 @@
 
 @decorator.cuda_test
 @decorator.pytorch_test
-@decorator.python_eol_test
 def test_pytorch_mixtral_8x7b():
-    """Test pytorch-mixtral-8x7b benchmark for fp8 inference."""
+    """Test pytorch-mixtral-8x7b benchmark for fp8 train and inference."""
     context = BenchmarkRegistry.create_benchmark_context(
         'mixtral-8x7b',
         platform=Platform.CUDA,
         parameters='--batch_size 1 --seq_len 32 --num_warmup 1 --num_steps 2 --precision fp8_e4m3 \
-            --model_action inference',
+            --hidden_size 1024 --max_position_embeddings 2048 --intermediate_size 3584 \
+            --model_action train inference',
         framework=Framework.PYTORCH
     )
 
@@ -36,13 +36,13 @@ def test_pytorch_mixtral_8x7b():
     assert (benchmark.name == 'pytorch-mixtral-8x7b')
     assert (benchmark.type == BenchmarkType.MODEL)
 
-    # Check predefined parameters of mixtral2 7b model.
-    assert (benchmark._args.hidden_size == 4096)
+    # Check predefined parameters of mixtral-8x7b model.
+    assert (benchmark._args.hidden_size == 1024)
     assert (benchmark._args.num_hidden_layers == 32)
     assert (benchmark._args.num_attention_heads == 32)
     assert (benchmark._args.num_key_value_heads == 8)
-    assert (benchmark._args.intermediate_size == 14336)
-    assert (benchmark._args.max_position_embeddings == 32768)
+    assert (benchmark._args.intermediate_size == 3584)
+    assert (benchmark._args.max_position_embeddings == 2048)
     assert (benchmark._args.router_aux_loss_coef == 0.02)
 
     # Check parameters specified in BenchmarkContext.