[model] Add support for openPangu_Ultra_MoE (vllm-project#27521)

Signed-off-by: yuantao <[email protected]>
Signed-off-by: yt0428 <[email protected]>
Co-authored-by: Jee Jee Li <[email protected]>

Author: 2 people

docs/models/supported_models.md

@@ -404,6 +404,8 @@ th {
 | `OPTForCausalLM` | OPT, OPT-IML | `facebook/opt-66b`, `facebook/opt-iml-max-30b`, etc. | ✅︎ | ✅︎ |
 | `OrionForCausalLM` | Orion | `OrionStarAI/Orion-14B-Base`, `OrionStarAI/Orion-14B-Chat`, etc. | | ✅︎ |
 | `OuroForCausalLM` | ouro | `ByteDance/Ouro-1.4B`, `ByteDance/Ouro-2.6B`, etc. | ✅︎ | |
+| `PanguEmbeddedForCausalLM` |openPangu-Embedded-7B | `FreedomIntelligence/openPangu-Embedded-7B-V1.1` | ✅︎ | ✅︎ |
+| `PanguUltraMoEForCausalLM` |openpangu-ultra-moe-718b-model | `FreedomIntelligence/openPangu-Ultra-MoE-718B-V1.1` | ✅︎ | ✅︎ |
 | `PhiForCausalLM` | Phi | `microsoft/phi-1_5`, `microsoft/phi-2`, etc. | ✅︎ | ✅︎ |
 | `Phi3ForCausalLM` | Phi-4, Phi-3 | `microsoft/Phi-4-mini-instruct`, `microsoft/Phi-4`, `microsoft/Phi-3-mini-4k-instruct`, `microsoft/Phi-3-mini-128k-instruct`, `microsoft/Phi-3-medium-128k-instruct`, etc. | ✅︎ | ✅︎ |
 | `PhiMoEForCausalLM` | Phi-3.5-MoE | `microsoft/Phi-3.5-MoE-instruct`, etc. | ✅︎ | ✅︎ |

tests/models/registry.py

@@ -363,13 +363,26 @@ def check_available_online(
     "Olmo2ForCausalLM": _HfExamplesInfo("allenai/OLMo-2-0425-1B"),
     "Olmo3ForCausalLM": _HfExamplesInfo("shanearora/2025-sep-a-base-model"),
     "OlmoeForCausalLM": _HfExamplesInfo("allenai/OLMoE-1B-7B-0924-Instruct"),
+    "OpenPanguMTPModel": _HfExamplesInfo(
+        "FreedomIntelligence/openPangu-Ultra-MoE-718B-V1.1",
+        trust_remote_code=True,
+        is_available_online=False,
+    ),
     "OPTForCausalLM": _HfExamplesInfo(
         "facebook/opt-125m", {"1b": "facebook/opt-iml-max-1.3b"}
     ),
     "OrionForCausalLM": _HfExamplesInfo(
         "OrionStarAI/Orion-14B-Chat", trust_remote_code=True
     ),
     "OuroForCausalLM": _HfExamplesInfo("ByteDance/Ouro-1.4B", trust_remote_code=True),
+    "PanguEmbeddedForCausalLM": _HfExamplesInfo(
+        "FreedomIntelligence/openPangu-Embedded-7B-V1.1", trust_remote_code=True
+    ),
+    "PanguUltraMoEForCausalLM": _HfExamplesInfo(
+        "FreedomIntelligence/openPangu-Ultra-MoE-718B-V1.1",
+        trust_remote_code=True,
+        is_available_online=False,
+    ),
     "PersimmonForCausalLM": _HfExamplesInfo("adept/persimmon-8b-chat"),
     "PhiForCausalLM": _HfExamplesInfo("microsoft/phi-2"),
     "Phi3ForCausalLM": _HfExamplesInfo("microsoft/Phi-3-mini-4k-instruct"),

vllm/config/model.py

@@ -1232,6 +1232,8 @@ def is_deepseek_mla(self) -> bool:
             "kimi_k2",
             "kimi_linear",
             "longcat_flash",
+            "pangu_ultra_moe",
+            "pangu_ultra_moe_mtp",
         ):
             return self.hf_text_config.kv_lora_rank is not None
         elif self.hf_text_config.model_type == "eagle":
@@ -1380,6 +1382,7 @@ def get_layers_start_end_indices(
             or self.hf_config.model_type == "glm4_moe_mtp"
             or self.hf_config.model_type == "ernie_mtp"
             or self.hf_config.model_type == "qwen3_next_mtp"
+            or self.hf_config.model_type == "pangu_ultra_moe_mtp"
         ):
             total_num_hidden_layers = getattr(
                 self.hf_text_config, "num_nextn_predict_layers", 0

vllm/config/speculative.py

@@ -41,6 +41,7 @@
     "qwen3_next_mtp",
     "mimo_mtp",
     "longcat_flash_mtp",
+    "pangu_ultra_moe_mtp",
     "mtp",
     "suffix",
 ]
@@ -51,6 +52,7 @@
     "ernie_mtp",
     "qwen3_next_mtp",
     "longcat_flash_mtp",
+    "pangu_ultra_moe_mtp",
 )
 
 
@@ -179,6 +181,13 @@ def hf_config_override(hf_config: PretrainedConfig) -> PretrainedConfig:
             hf_config.update(
                 {"n_predict": n_predict, "architectures": ["DeepSeekMTPModel"]}
             )
+        if hf_config.model_type in ("pangu_ultra_moe"):
+            hf_config.model_type = "pangu_ultra_moe_mtp"
+        if hf_config.model_type == "pangu_ultra_moe_mtp":
+            n_predict = getattr(hf_config, "num_nextn_predict_layers", None)
+            hf_config.update(
+                {"n_predict": n_predict, "architectures": ["OpenPanguMTPModel"]}
+            )
 
         if hf_config.architectures[0] == "MiMoForCausalLM":
             hf_config.model_type = "mimo_mtp"