diff --git a/vllm/v1/sample/rejection_sampler.py b/vllm/v1/sample/rejection_sampler.py
index 678654cb78a4..89cf47e8fdaa 100644
--- a/vllm/v1/sample/rejection_sampler.py
+++ b/vllm/v1/sample/rejection_sampler.py
@@ -62,9 +62,11 @@ def __init__(
         sampler: Sampler,
         spec_config: SpeculativeConfig | None = None,
         device: torch.device | None = None,
+        eos_token_ids: list[int] | None = None,
     ):
         super().__init__()
         self.sampler = sampler
+        self.eos_token_ids = eos_token_ids
         logprobs_mode = self.sampler.logprobs_mode
         self.is_processed_logprobs_mode = logprobs_mode.startswith("processed")
         self.is_logits_logprobs_mode = logprobs_mode.endswith("logits")
@@ -165,6 +167,17 @@ def forward(
             sampling_metadata,
         )
 
+        # Suppress EOS at draft positions so MTP speculative decoding
+        # doesn't prematurely terminate tool-call generation.
+        # Use scalar column indexing (select + fill_) instead of list
+        # indexing to avoid the indexSelectSmallIndex CUDA kernel which
+        # can assert with large vocab sizes.
+        if self.eos_token_ids:
+            vocab_size = target_logits.shape[-1]
+            for eid in self.eos_token_ids:
+                if 0 <= eid < vocab_size:
+                    target_logits[:, eid].fill_(float('-inf'))
+
         output_token_ids = rejection_sample(
             metadata.draft_token_ids,
             metadata.num_draft_tokens,
diff --git a/vllm/v1/worker/gpu_model_runner.py b/vllm/v1/worker/gpu_model_runner.py
index bcab2ca2d4c2..740057277b99 100644
--- a/vllm/v1/worker/gpu_model_runner.py
+++ b/vllm/v1/worker/gpu_model_runner.py
@@ -218,6 +218,25 @@
 
 logger = init_logger(__name__)
 
+
+def _collect_eos_token_ids(model_config) -> list[int] | None:
+    ids: set[int] = set()
+    for cfg in (model_config.hf_config, model_config.hf_text_config):
+        val = getattr(cfg, 'eos_token_id', None)
+        if val is not None:
+            if isinstance(val, int):
+                ids.add(val)
+            else:
+                ids.update(val)
+    gen_config = model_config.try_get_generation_config()
+    if gen_config and (val := gen_config.get('eos_token_id')) is not None:
+        if isinstance(val, int):
+            ids.add(val)
+        else:
+            ids.update(val)
+    return sorted(ids) if ids else None
+
+
 AttnMetadataDict: TypeAlias = dict[str, AttentionMetadata]
 # list when ubatching is enabled
 PerLayerAttnMetadata: TypeAlias = list[AttnMetadataDict] | AttnMetadataDict
@@ -578,7 +597,8 @@ def __init__(
                     f"{self.speculative_config.method}"
                 )
             self.rejection_sampler = RejectionSampler(
-                self.sampler, self.speculative_config, self.device
+                self.sampler, self.speculative_config, self.device,
+                eos_token_ids=_collect_eos_token_ids(self.model_config),
             )
 
         self.num_spec_tokens = 0