diff --git a/docs/docs/hardware-platforms/ascend-npus/optimization/parameter_tuning.mdx b/docs/docs/hardware-platforms/ascend-npus/optimization/parameter_tuning.mdx
index 211521915..b4874b473 100644
--- a/docs/docs/hardware-platforms/ascend-npus/optimization/parameter_tuning.mdx
+++ b/docs/docs/hardware-platforms/ascend-npus/optimization/parameter_tuning.mdx
@@ -767,6 +767,8 @@ Captures the compute graph on NPU and replays it to eliminate kernel launch over
 
 Reduces per-token latency by predicting multiple future tokens in a single forward pass, then verifying them against the model. Ascend supports `NEXTN` (for DeepSeek models, using the model's own hidden states) and `EAGLE3` (for Qwen MoE models, using a separate draft model). Controlled by `--speculative-num-steps`, `--speculative-eagle-topk`, and `--speculative-num-draft-tokens`. On Ascend, `SGLANG_ENABLE_OVERLAP_PLAN_STREAM=1` enables the optimized overlap scheduler for speculative decoding.
 
+For non-greedy requests, Ascend target verification applies request-level `temperature`, `top_k`, and `top_p`. The default target-only mode supports linear and tree-shaped candidates. Classic rejection sampling is available with `--speculative-use-rejection-sampling` for linear chains configured with `--speculative-eagle-topk 1`.
+
 ### PrefixCache (`--disable-radix-cache`)
 
 Reuses KV cache across requests that share common prompt prefixes (Radix Cache), reducing repeated prefill computation and lowering time-to-first-token. Enabled by default; disable with `--disable-radix-cache` when prefix reuse is not expected (e.g., dedicated prefill nodes in PD disaggregation, or random-input benchmarks).
diff --git a/docs/docs/hardware-platforms/ascend-npus/reference/support_features.mdx b/docs/docs/hardware-platforms/ascend-npus/reference/support_features.mdx
index a754f6f8d..419c0014a 100644
--- a/docs/docs/hardware-platforms/ascend-npus/reference/support_features.mdx
+++ b/docs/docs/hardware-platforms/ascend-npus/reference/support_features.mdx
@@ -1373,6 +1373,16 @@ click [Server Arguments](../../../advanced_features/server_arguments).
 
 ## Speculative decoding
 
+Ascend NPU supports non-greedy target verification for the supported EAGLE-based speculative algorithms. Request-level
+`temperature`, `top_k`, and `top_p` are applied when constructing the target probability distribution. Request-level
+`top_k` controls token sampling and is separate from `--speculative-eagle-topk`, which controls the draft tree branching
+factor.
+
+The default target-only mode supports both linear and tree-shaped draft candidates. Classic rejection sampling is
+available for EAGLE3 and NEXTN with `--speculative-use-rejection-sampling` and requires
+`--speculative-eagle-topk 1`. Rejection sampling uses the draft proposal distribution and cannot be combined with
+non-default speculative acceptance thresholds or deterministic inference.
+
 <table style={{width: "100%", borderCollapse: "collapse", tableLayout: "fixed"}}>
   <colgroup>
     <col style={{width: "16.7%"}} />
@@ -1443,13 +1453,19 @@ click [Server Arguments](../../../advanced_features/server_arguments).
       <td style={{padding: "9px 12px", fontWeight: 500, backgroundColor: "rgba(255,255,255,0.02)"}}>`--speculative-accept-threshold-single`</td>
       <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>`1.0`</td>
       <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.02)"}}>Type: float</td>
-      <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>Special for GPU</td>
+      <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>A2, A3</td>
     </tr>
     <tr>
       <td style={{padding: "9px 12px", fontWeight: 500, backgroundColor: "rgba(255,255,255,0.02)"}}>`--speculative-accept-threshold-acc`</td>
       <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>`1.0`</td>
       <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.02)"}}>Type: float</td>
-      <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>Special for GPU</td>
+      <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>A2, A3</td>
+    </tr>
+    <tr>
+      <td style={{padding: "9px 12px", fontWeight: 500, backgroundColor: "rgba(255,255,255,0.02)"}}>`--speculative-use-rejection-sampling`</td>
+      <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>`False`</td>
+      <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.02)"}}>bool flag<br/> (requires `--speculative-eagle-topk 1`)</td>
+      <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>A2, A3</td>
     </tr>
     <tr>
       <td style={{padding: "9px 12px", fontWeight: 500, backgroundColor: "rgba(255,255,255,0.02)"}}>`--speculative-token-map`</td>
diff --git a/python/sglang/srt/speculative/eagle_utils.py b/python/sglang/srt/speculative/eagle_utils.py
index 99875779b..616f808d7 100644
--- a/python/sglang/srt/speculative/eagle_utils.py
+++ b/python/sglang/srt/speculative/eagle_utils.py
@@ -781,7 +781,7 @@ def eagle_sample(
 
     # Sample tokens
     target_predict = None
-    if sampling_info.is_all_greedy or _is_cpu or _is_npu or _is_hip or _is_xpu:
+    if sampling_info.is_all_greedy or _is_cpu or _is_hip or _is_xpu:
         target_predict = torch.argmax(next_token_logits, dim=-1)
         target_predict = target_predict.reshape(bs, verify_input.draft_token_num)
         predict, accept_index, num_correct_drafts = verify_tree_greedy_func(
@@ -847,15 +847,23 @@ def eagle_sample(
             tp_group.broadcast(accept_index, src=0)
             tp_group.broadcast(num_correct_drafts, src=0)
     else:
-        from sgl_kernel import (
-            top_k_renorm_prob,
-            top_p_renorm_prob,
-            tree_speculative_sampling_target_only,
-        )
+        if _is_npu:
+            from sgl_kernel_npu.sample import (
+                chain_speculative_sampling_triton,
+                top_k_renorm_prob,
+                top_p_renorm_prob,
+                tree_speculative_sampling_target_only,
+            )
+        else:
+            from sgl_kernel import (
+                top_k_renorm_prob,
+                top_p_renorm_prob,
+                tree_speculative_sampling_target_only,
+            )
 
-        from sglang.kernels.ops.speculative.reject_sampling import (
-            chain_speculative_sampling_triton,
-        )
+            from sglang.kernels.ops.speculative.reject_sampling import (
+                chain_speculative_sampling_triton,
+            )
 
         use_rejection_sampling = get_spec().speculative_use_rejection_sampling