diff --git a/vllm/tokenizers/hf.py b/vllm/tokenizers/hf.py
index a7b565dca5d8..596b3bdbc623 100644
--- a/vllm/tokenizers/hf.py
+++ b/vllm/tokenizers/hf.py
@@ -7,12 +7,16 @@
 
 from transformers import AutoTokenizer, PreTrainedTokenizer, PreTrainedTokenizerFast
 
+from vllm.logger import init_logger
 from vllm.transformers_utils.config import get_sentence_transformer_tokenizer_config
+from vllm.transformers_utils.gguf_utils import extract_eos_token_id_from_gguf
 
 from .protocol import TokenizerLike
 
 HfTokenizer: TypeAlias = PreTrainedTokenizer | PreTrainedTokenizerFast
 
+logger = init_logger(__name__)
+
 
 def get_cached_tokenizer(tokenizer: HfTokenizer) -> HfTokenizer:
     """
@@ -75,6 +79,9 @@ def from_pretrained(
         download_dir: str | None = None,
         **kwargs,
     ) -> HfTokenizer:
+        # Save gguf_file before AutoTokenizer.from_pretrained() pops it from kwargs
+        gguf_file = kwargs.get("gguf_file")
+
         try:
             tokenizer = AutoTokenizer.from_pretrained(
                 path_or_repo_id,
@@ -116,4 +123,23 @@ def from_pretrained(
             }
             tokenizer.add_special_tokens(special_tokens_map)
 
+        # Patch EOS token ID from GGUF metadata if available
+        # GGUF files may have a different EOS token ID than HF tokenizer config
+        # (e.g., Gemma uses <end_of_turn> ID 106 as EOS, but HF reports <eos> ID 1)
+        # Note: gguf_file was saved above before
+        # AutoTokenizer.from_pretrained() popped it
+        if gguf_file:
+            gguf_path = Path(path_or_repo_id) / gguf_file
+            gguf_eos_id = extract_eos_token_id_from_gguf(str(gguf_path))
+            if gguf_eos_id is not None:
+                hf_eos_id = tokenizer.eos_token_id
+                if hf_eos_id != gguf_eos_id:
+                    logger.info(
+                        "Patching tokenizer eos_token_id from %d to %d "
+                        "(using GGUF metadata)",
+                        hf_eos_id,
+                        gguf_eos_id,
+                    )
+                    tokenizer.eos_token_id = gguf_eos_id
+
         return get_cached_tokenizer(tokenizer)
diff --git a/vllm/transformers_utils/gguf_utils.py b/vllm/transformers_utils/gguf_utils.py
index 3faa5ee60e9f..321011628678 100644
--- a/vllm/transformers_utils/gguf_utils.py
+++ b/vllm/transformers_utils/gguf_utils.py
@@ -220,6 +220,46 @@ def extract_vision_config_from_gguf(mmproj_path: str) -> "SiglipVisionConfig | N
     return config
 
 
+def extract_eos_token_id_from_gguf(model: str) -> int | None:
+    """Extract EOS token ID from GGUF metadata.
+
+    GGUF files store the EOS token ID in tokenizer.ggml.eos_token_id field.
+    This may differ from HuggingFace's tokenizer config (e.g., Gemma models
+    use <end_of_turn> token ID 106 as EOS in GGUF, but HF tokenizer reports
+    <eos> token ID 1).
+
+    Args:
+        model: Path to GGUF model file
+
+    Returns:
+        EOS token ID from GGUF metadata, or None if not found
+    """
+    # Note: We don't check for .gguf extension here because HuggingFace Hub
+    # stores GGUF files as blob hashes without extensions. The caller is
+    # responsible for ensuring this is a valid GGUF file (via check_gguf_file).
+    try:
+        model_path = Path(model)
+        if not model_path.is_file():
+            return None
+
+        reader = gguf.GGUFReader(str(model_path))
+
+        eos_field = reader.get_field(Keys.Tokenizer.EOS_ID)
+        if eos_field is not None:
+            eos_token_id = int(eos_field.parts[-1][0])
+            logger.debug(
+                "Extracted eos_token_id=%d from GGUF metadata",
+                eos_token_id,
+            )
+            return eos_token_id
+
+        return None
+
+    except Exception as e:
+        logger.debug("Error extracting EOS token ID from GGUF: %s", e)
+        return None
+
+
 def maybe_patch_hf_config_from_gguf(
     model: str,
     hf_config: PretrainedConfig,