diff --git a/tests/samplers/test_logits_processor.py b/tests/samplers/test_logits_processor.py
new file mode 100644
index 0000000000000..3788e9e9752ff
--- /dev/null
+++ b/tests/samplers/test_logits_processor.py
@@ -0,0 +1,62 @@
+import pytest
+import torch
+
+from vllm import SamplingParams
+
+MODELS = ["facebook/opt-125m"]
+
+
+@pytest.mark.parametrize("model", MODELS)
+@pytest.mark.parametrize("dtype", ["half"])
+def test_logits_processor_force_generate(
+    vllm_runner,
+    example_prompts,
+    model: str,
+    dtype: str,
+) -> None:
+    vllm_model = vllm_runner(model, dtype=dtype)
+    tokenizer = vllm_model.model.get_tokenizer()
+    repeat_times = 2
+    enforced_answers = " vLLM"
+    vllm_token_ids = tokenizer.encode(enforced_answers,
+                                      add_special_tokens=False)
+    max_tokens = len(vllm_token_ids) * repeat_times
+
+    def pick_vllm(token_ids, logits):
+        token_id = vllm_token_ids[len(token_ids) % len(vllm_token_ids)]
+        logits[token_id] = torch.finfo(logits.dtype).max
+        return logits
+
+    params_with_logprobs = SamplingParams(
+        logits_processors=[pick_vllm],
+        prompt_logprobs=3,
+        max_tokens=max_tokens,
+    )
+
+    # test logits_processors when prompt_logprobs is not None
+    vllm_model.model._add_request(
+        prompt=example_prompts[0],
+        sampling_params=params_with_logprobs,
+        prompt_token_ids=None,
+    )
+
+    # test prompt_logprobs is not None
+    vllm_model.model._add_request(
+        prompt=example_prompts[1],
+        sampling_params=SamplingParams(
+            prompt_logprobs=3,
+            max_tokens=max_tokens,
+        ),
+        prompt_token_ids=None,
+    )
+
+    # test grouped requests
+    vllm_model.model._add_request(
+        prompt=example_prompts[2],
+        sampling_params=SamplingParams(max_tokens=max_tokens),
+        prompt_token_ids=None,
+    )
+
+    outputs = vllm_model.model._run_engine(False)
+
+    assert outputs[0].outputs[0].text == enforced_answers * repeat_times
diff --git a/vllm/model_executor/layers/logits_processor.py b/vllm/model_executor/layers/logits_processor.py
index 28e8f6bb7e638..ec531f79ced52 100644
--- a/vllm/model_executor/layers/logits_processor.py
+++ b/vllm/model_executor/layers/logits_processor.py
@@ -86,8 +86,16 @@ def _apply_logits_processors(
 ) -> torch.Tensor:
     logits_row_idx = 0
     found_logits_processors = False
-    for seq_ids, sampling_params in sampling_metadata.seq_groups:
+    for i, seq_group in enumerate(sampling_metadata.seq_groups):
+        seq_ids, sampling_params = seq_group
         logits_processors = sampling_params.logits_processors
+        # handle prompt_logprobs by skipping rows in logits added for
+        # the prompt tokens (prompt logprobs are not processed)
+        if (i < sampling_metadata.num_prompts
+                and sampling_params.prompt_logprobs is not None):
+            assert len(seq_ids) == 1
+            logits_row_idx += sampling_metadata.prompt_lens[i] - 1
+
         if logits_processors:
             found_logits_processors = True
             for seq_id in seq_ids:
@@ -100,5 +108,6 @@ def _apply_logits_processors(
         else:
             logits_row_idx += len(seq_ids)
     if found_logits_processors:
+        # verifies that no rows in logits were missed unexpectedly
         assert logits_row_idx == logits.shape[0]
     return logits