diff --git a/src/tests/python_tests/test_cpp_samples.py b/src/tests/python_tests/test_cpp_samples.py
deleted file mode 100644
index 85ab4a9fbd..0000000000
--- a/src/tests/python_tests/test_cpp_samples.py
+++ /dev/null
@@ -1,85 +0,0 @@
-
-import pytest
-
-model_ids = [
-    # ("TinyLlama/TinyLlama-1.1B-Chat-v1.0", "TinyLlama-1.1B-Chat-v1.0-skip-special-tokens"),
-
-    ("TinyLlama/TinyLlama-1.1B-Chat-v1.0", "TinyLlama-1.1B-Chat-v1.0/pytorch/dldt/FP16/"),
-    ("google/gemma-2b-it", "gemma-2b-it/pytorch/dldt/FP16/"),
-    # ("meta-llama/Llama-2-7b-chat-hf", "Llama-2-7b-chat-hf/pytorch/dldt/FP16/"),
-]
-
-def run_cpp_sample_command(command, cwd):
-    import subprocess
-    process = subprocess.Popen(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, cwd=cwd, text=True)
-    stdout, stderr = process.communicate()
-    return stdout, stderr, process.returncode
-
-def run_transformers_model(model_id, prompt, config=None, add_special_tokens=True):
-    import transformers
-
-    tokenizer = transformers.AutoTokenizer.from_pretrained(model_id)
-    model = transformers.AutoModelForCausalLM.from_pretrained(model_id)
-    tokenized = tokenizer.encode(prompt, return_tensors='pt', add_special_tokens=add_special_tokens)
-        
-    default_config = dict( 
-        num_beam_groups=3, 
-        num_beams=15, 
-        diversity_penalty=1.0, 
-        num_return_sequences=15, 
-        max_new_tokens=20, 
-        early_stopping=False, 
-        length_penalty=1.0, 
-        no_repeat_ngram_size=9**9, 
-        do_sample=False
-    )
-
-    if config is None:
-        config = default_config
-    print(tokenized)
-    beams = model.generate(tokenized, **config)
-    return map(lambda beam: tokenizer.decode(beam[tokenized.numel():], skip_special_tokens=True), beams)
-
-@pytest.mark.parametrize("param", model_ids)
-def test_model(param):
-    model_id, path = param
-
-    prompts = ["table is made of", "The Sun is yellow because"]
-    # prompt = " ".join([f'"{item}"' for item in prompts])
-
-    prompt = "table is made of"
-
-    # cmd = 'build-Debug/greedy_causal_lm' // for old samples
-    cmd = 'build-Debug/text_generation/causal_lm/cpp/'
-    
-    # beam search old
-    cmd = 'build-Debug/beam_search_causal_lm'
-    cwd = '/home/epavel/devel/openvino.genai_'
-    config = None # None means greedy
-
-    # greedy new
-    cwd = '/home/epavel/devel/openvino.genai'
-    cmd = 'build-Debug/text_generation/causal_lm/cpp/greedy_causal_lm'
-    config = dict(max_new_tokens=75, do_sample=False)
-
-    # beam search new
-    cwd = '/home/epavel/devel/openvino.genai'
-    cmd = 'build-Debug/text_generation/causal_lm/cpp/beam_search_causal_lm'
-    config = None
-
-    predictions, _, _ = run_cpp_sample_command([cmd, '/home/epavel/devel/openvino.genai/text_generation/causal_lm/' + path, prompt], cwd)
-    print(predictions)
-    
-    beams = run_transformers_model(model_id, prompt, config)
-    for beam in beams:
-        idx = predictions.find(beam)
-        if -1 == idx and beam and predictions:
-            raise RuntimeError(f'Missing "{beam=}" from predictions')
-        predictions = predictions[:idx] + predictions[idx + len(beam):]
-    
-    return True
-    # with open('pred.txt', 'r') as file:
-    #     predictions = file.read()
-
-for model_id, path in model_ids:
-    test_model((model_id, path))