Add acceptance length reference values for deepseek model

MODELS.md

@@ -108,7 +108,7 @@ The table also records both the agreed plan-of-record (PoR) draft-model mapping
 
 | Model | Primary native/upstream engines | Agreed draft model(s) (PoR) | Proposed draft model(s) pending partner alignment | Additional engines |
 |---|---|---|---|---|
-| DeepSeek-V4-Pro 1.6T (`dsv4`) | native/upstream vLLM engine and native/upstream SGLang engine | native MTP | `deepseek-ai/DeepSeek-V4-Pro-DSpark`, proposed for AgentX only under the same synthetic-acceptance methodology and pending partner alignment. Single-turn 8k1k remains on the native MTP heads. | Additional non-vLLM/SGLang engines under the ordering guideline and exceptions above |
+| DeepSeek-V4-Pro 1.6T (`dsv4`) | native/upstream vLLM engine and native/upstream SGLang engine | native MTP (Single-turn 8k1k); native DSpark heads `deepseek-ai/DeepSeek-V4-Pro-0813` (Agentic coding only, under the same synthetic-acceptance methodology as Kimi-K3's DSpark PoR) | None | Additional non-vLLM/SGLang engines under the ordering guideline and exceptions above |
 | Kimi-K3 (`kimik3`) | native/upstream vLLM engine | `Inferact/Kimi-K3-DSpark` | None | Additional non-vLLM/SGLang engines under the ordering guideline and exceptions above |
 | MiniMax-M3 (`minimaxm3`) | native/upstream vLLM engine | `Inferact/MiniMax-M3-EAGLE3` and/or `Inferact/MiniMax-M3-EAGLE3-GQA` | None | Additional non-vLLM/SGLang engines under the ordering guideline and exceptions above |
 | GLM-5.2 (`glm5.2`) | native/upstream SGLang engine | native MTP | None | Additional non-vLLM/SGLang engines under the ordering guideline and exceptions above |

MODELS_zh.md

@@ -108,7 +108,7 @@ InferenceX 支持 SGLang 和 vLLM 双方的维护者，并响应 AI 实验室和
 
 | 模型 | 首选原生/上游引擎 | 已达成一致的草稿模型（PoR） | 待合作伙伴对齐的草稿模型提案 | 其他引擎 |
 |---|---|---|---|---|
-| DeepSeek-V4-Pro 1.6T（`dsv4`） | 原生/上游 vLLM 引擎和原生/上游 SGLang 引擎 | 原生 MTP | `deepseek-ai/DeepSeek-V4-Pro-DSpark`，仅提议用于 AgentX，并须遵循相同的合成接受方法，尚待合作伙伴对齐。单轮 8k1k 继续使用原生 MTP 头。 | 按照上述提交顺序指南及例外处理的其他非 vLLM/SGLang 引擎 |
+| DeepSeek-V4-Pro 1.6T（`dsv4`） | 原生/上游 vLLM 引擎和原生/上游 SGLang 引擎 | 原生 MTP（单轮 8k1k）；`deepseek-ai/DeepSeek-V4-Pro-0813`（仅用于智能体编码，遵循与 Kimi-K3 DSpark PoR 相同的合成接受方法） | 无 | 按照上述提交顺序指南及例外处理的其他非 vLLM/SGLang 引擎 |
 | Kimi-K3（`kimik3`） | 原生/上游 vLLM 引擎 | `Inferact/Kimi-K3-DSpark` | 无 | 按照上述提交顺序指南及例外处理的其他非 vLLM/SGLang 引擎 |
 | MiniMax-M3（`minimaxm3`） | 原生/上游 vLLM 引擎 | `Inferact/MiniMax-M3-EAGLE3` 和/或 `Inferact/MiniMax-M3-EAGLE3-GQA` | 无 | 按照上述提交顺序指南及例外处理的其他非 vLLM/SGLang 引擎 |
 | GLM-5.2（`glm5.2`） | 原生/上游 SGLang 引擎 | 原生 MTP | 无 | 按照上述提交顺序指南及例外处理的其他非 vLLM/SGLang 引擎 |

golden_al_distribution/dsv4-pro-0813-dspark.yaml

@@ -0,0 +1,19 @@
+# Source GitHub Actions run: https://github.com/SemiAnalysisAI/InferenceX/actions/runs/31742838308
+# Acceptance Length (AL) reference values measured with SPEED-Bench.
+# dataset: coding | temperature: 1.0 | output_len: 4096
+# thinking_on chat_template_kwargs: {"thinking": true, "reasoning_effort": "high"}
+# speculative-config: method=dspark | draft_sample_method=probabilistic
+# Measured on deepseek-v4-pro-0813 (B300, vLLM DSpark), per num_speculative_tokens.
+# Auto-generated by benchmarks/single_node/speedbench/dsv4dspark_fp4_b300_vllm.sh (speedbench-al.yml).
+#
+# key = num_speculative_tokens (DSpark level); value = golden AL
+deepseek-v4-pro-0813:
+  thinking_on:
+    1: 1.84
+    2: 2.51
+    3: 3.01
+    4: 3.36
+    5: 3.61
+    6: 3.77
+    7: 3.73
+    8: 3.47

runners/inject_synthetic_acceptance.py

@@ -40,6 +40,10 @@
 MODEL_PREFIX_TO_YAML_KEY = {
     "dsv4": "deepseek-v4-pro",
     "dsr1": "deepseek-r1",
+    # DSpark ships as its own checkpoint (deepseek-ai/DeepSeek-V4-Pro-DSpark,
+    # dated 0813), distinct from the plain MTP checkpoint above.
+    "dsv4dspark": "deepseek-v4-pro-0813",
+    "dsv4dsparkprob": "deepseek-v4-pro-0813",
 }