diff --git a/samples/cpp/continuous_batching_accuracy/continuous_batching_accuracy.cpp b/samples/cpp/continuous_batching_accuracy/continuous_batching_accuracy.cpp
index 6e0cb5034f..0561f88179 100644
--- a/samples/cpp/continuous_batching_accuracy/continuous_batching_accuracy.cpp
+++ b/samples/cpp/continuous_batching_accuracy/continuous_batching_accuracy.cpp
@@ -39,16 +39,13 @@ int main(int argc, char* argv[]) try {
 
     const size_t num_prompts = result["num_prompts"].as<size_t>();
     const bool dynamic_split_fuse = result["dynamic_split_fuse"].as<bool>();
-    const std::string models_path = result["model"].as<std::string>();
+    const std::string models_path = "/home/panas/llm/models/TinyLlama-1.1B-Chat-v1.0/";
 
     // create dataset
 
     std::vector<std::string> prompt_examples = {
-        "What is OpenVINO?",
-        "How are you?",
-        "What is your name?",
-        "Tell me something about Canada",
-        "What is OpenVINO?",
+        "hello",
+        "Here is the longest novel ever: "
     };
 
     std::vector<ov::genai::GenerationConfig> sampling_params_examples {
@@ -57,7 +54,7 @@ int main(int argc, char* argv[]) try {
         ov::genai::multinomial(),
     };
 
-    std::vector<std::string> prompts(num_prompts);
+    std::vector<std::string> prompts(2);
     std::vector<ov::genai::GenerationConfig> sampling_params(num_prompts);
 
     for (size_t request_id = 0; request_id < num_prompts; ++request_id) {
@@ -79,7 +76,49 @@ int main(int argc, char* argv[]) try {
     scheduler_config.max_num_seqs = 2;
 
     ov::genai::ContinuousBatchingPipeline pipe(models_path, scheduler_config);
-    std::vector<ov::genai::GenerationResult> generation_results = pipe.generate(prompts, sampling_params);
+    ov::genai::GenerationConfig prototype;
+    prototype.max_new_tokens = 20;
+    prototype.num_beam_groups = 3;
+    prototype.num_beams = 15;
+    prototype.diversity_penalty = 1.0;
+    std::vector<ov::genai::GenerationResult> generation_results = pipe.generate({
+        "hello",
+        "Here is the longest novel ever: "
+    }, std::vector(2, prototype));
+
+
+    for (size_t request_id = 0; request_id < generation_results.size(); ++request_id) {
+        const ov::genai::GenerationResult & generation_result = generation_results[request_id];
+        std::cout << "Question: " << prompts[request_id] << std::endl;
+        switch (generation_result.m_status)
+        {
+        case ov::genai::GenerationStatus::FINISHED:
+            print_generation_result(generation_result);
+            break;
+        case ov::genai::GenerationStatus::IGNORED:
+            std::cout << "Request was ignored due to lack of memory." <<std::endl;
+            if (generation_result.m_generation_ids.size() > 0) {
+                std::cout << "Partial result:" << std::endl;
+                print_generation_result(generation_result);
+            }
+            break;
+        case ov::genai::GenerationStatus::DROPPED_BY_PIPELINE:
+            std::cout << "Request was aborted." <<std::endl;
+            if (generation_result.m_generation_ids.size() > 0) {
+                std::cout << "Partial result:" << std::endl;
+                print_generation_result(generation_result);
+            }
+            break;   
+        default:
+            break;
+        }
+        std::cout << std::endl;
+    }
+
+    generation_results = pipe.generate({
+        "hello",
+        "Here is the longest novel ever: "
+    }, std::vector(2, prototype));
 
     for (size_t request_id = 0; request_id < generation_results.size(); ++request_id) {
         const ov::genai::GenerationResult & generation_result = generation_results[request_id];