diff --git a/lmdeploy/cli/serve.py b/lmdeploy/cli/serve.py
index 01ac1d44f1..e11bb359ba 100644
--- a/lmdeploy/cli/serve.py
+++ b/lmdeploy/cli/serve.py
@@ -92,6 +92,7 @@ def add_parser_api_server():
         # model args
         ArgumentHelper.revision(parser)
         ArgumentHelper.download_dir(parser)
+        ArgumentHelper.generation_config(parser)
 
         # pytorch engine args
         pt_group = parser.add_argument_group('PyTorch engine arguments')
@@ -318,6 +319,7 @@ def api_server(args):
                 reasoning_parser=args.reasoning_parser,
                 tool_call_parser=args.tool_call_parser,
                 speculative_config=speculative_config,
+                generation_config=args.generation_config,
             )
         else:
             from lmdeploy.serve.openai.launch_server import launch_server
@@ -350,6 +352,7 @@ def api_server(args):
                 reasoning_parser=args.reasoning_parser,
                 tool_call_parser=args.tool_call_parser,
                 speculative_config=speculative_config,
+                generation_config=args.generation_config,
             )
 
     @staticmethod
diff --git a/lmdeploy/cli/utils.py b/lmdeploy/cli/utils.py
index 1dda62a7e8..12f726700a 100644
--- a/lmdeploy/cli/utils.py
+++ b/lmdeploy/cli/utils.py
@@ -301,6 +301,18 @@ def hf_overrides(parser):
                                    default=None,
                                    help='Extra arguments to be forwarded to the HuggingFace config.')
 
+    @staticmethod
+    def generation_config(parser):
+        """Add argument generation_config to parser."""
+        return parser.add_argument(
+            '--generation-config',
+            type=str,
+            default='auto',
+            help='The folder path to the generation config. Defaults to "auto", the '
+            'generation config will be loaded from model path. If set to "lmdeploy", no '
+            'generation config is loaded, lmdeploy defaults will be used. If set to a folder '
+            'path, the generation config will be loaded from the specified folder path.')
+
     @staticmethod
     def use_logn_attn(parser):
         """Add argument use_logn_attn to parser."""
diff --git a/lmdeploy/serve/anthropic/adapter.py b/lmdeploy/serve/anthropic/adapter.py
index 6975c7c8ad..c1b2553897 100644
--- a/lmdeploy/serve/anthropic/adapter.py
+++ b/lmdeploy/serve/anthropic/adapter.py
@@ -9,6 +9,7 @@
 import shortuuid
 
 from lmdeploy.messages import GenerationConfig
+from lmdeploy.serve.core.generation_config import build_generation_config
 from lmdeploy.serve.openai.protocol import Tool, ToolChoice, ToolChoiceFuncName
 
 from .protocol import (
@@ -341,15 +342,15 @@ def to_lmdeploy_messages(request: MessagesRequest | CountTokensRequest) -> list[
     return lm_messages
 
 
-def to_generation_config(request: MessagesRequest) -> GenerationConfig:
+def to_generation_config(
+    request: MessagesRequest,
+    default_gen_config: dict | None = None,
+) -> GenerationConfig:
     """Map Anthropic messages request to LMDeploy generation config."""
-
-    return GenerationConfig(
+    return build_generation_config(
+        request,
+        default_gen_config or {},
         max_new_tokens=request.max_tokens,
-        do_sample=True,
-        top_k=40 if request.top_k is None else request.top_k,
-        top_p=1.0 if request.top_p is None else request.top_p,
-        temperature=1.0 if request.temperature is None else request.temperature,
         stop_words=request.stop_sequences,
         include_stop_str_in_output=request.include_stop_str_in_output or False,
         skip_special_tokens=True,
diff --git a/lmdeploy/serve/anthropic/endpoints/messages.py b/lmdeploy/serve/anthropic/endpoints/messages.py
index 1f5b17a54b..6027fb3030 100644
--- a/lmdeploy/serve/anthropic/endpoints/messages.py
+++ b/lmdeploy/serve/anthropic/endpoints/messages.py
@@ -174,7 +174,10 @@ async def create_message(request: MessagesRequest, raw_request: Request):
         result_generator = server_context.async_engine.generate(
             engine_messages,
             session,
-            gen_config=to_generation_config(request),
+            gen_config=to_generation_config(
+                request,
+                default_gen_config=server_context.default_gen_config,
+            ),
             tools=parsed_request.tools,
             stream_response=True,
             sequence_start=True,
diff --git a/lmdeploy/serve/anthropic/protocol.py b/lmdeploy/serve/anthropic/protocol.py
index 03f0b1c37f..37fa0f7bd7 100644
--- a/lmdeploy/serve/anthropic/protocol.py
+++ b/lmdeploy/serve/anthropic/protocol.py
@@ -104,7 +104,7 @@ class MessagesRequest(BaseModel):
     system: str | list[ContentBlockParam] | None = None
     stop_sequences: list[str] | None = None
     stream: bool = False
-    temperature: float | None = 1.0
+    temperature: float | None = None
     top_p: float | None = None
     top_k: int | None = None
     metadata: dict[str, Any] | None = None
diff --git a/lmdeploy/serve/core/generation_config.py b/lmdeploy/serve/core/generation_config.py
new file mode 100644
index 0000000000..82126af92c
--- /dev/null
+++ b/lmdeploy/serve/core/generation_config.py
@@ -0,0 +1,94 @@
+# Copyright (c) OpenMMLab. All rights reserved.
+"""Server-side generation config resolution and sampling parameter merge
+helpers."""
+
+from __future__ import annotations
+
+import dataclasses
+from typing import Any
+
+from lmdeploy.messages import GenerationConfig
+from lmdeploy.utils import get_logger
+
+logger = get_logger('lmdeploy')
+
+
+def _load_hf_generation_config(path: str, trust_remote_code: bool) -> dict[str, Any]:
+    from transformers import GenerationConfig
+
+    try:
+        cfg = GenerationConfig.from_pretrained(path, trust_remote_code=trust_remote_code)
+        return cfg.to_diff_dict()
+    except OSError:
+        return {}
+
+
+def resolve_default_gen_config(
+    generation_config: str,
+    model_path: str,
+    trust_remote_code: bool,
+) -> dict[str, Any]:
+    """Resolve server-side default generation config from CLI flags."""
+    src = generation_config
+
+    if src == 'lmdeploy':
+        config: dict[str, Any] = {}
+    elif src == 'auto':
+        config = _load_hf_generation_config(model_path, trust_remote_code)
+    else:
+        config = _load_hf_generation_config(src, trust_remote_code)
+
+    if config and src != 'lmdeploy':
+        source = "the model's `generation_config.json`" if src == 'auto' else src
+        logger.info(
+            f'Using default generation config from {source}: {config}. '
+            'Use `--generation-config lmdeploy` to disable.')
+
+    return config
+
+
+def merge_sampling_params(
+    request_values: dict[str, Any],
+    default_gen_config: dict[str, Any],
+) -> dict[str, Any]:
+    """Merge sampling params with request > default_gen_config priority."""
+    merged: dict[str, Any] = {}
+    for key in set(default_gen_config) | set(request_values):
+        if key in request_values:
+            merged[key] = request_values[key]
+        else:
+            merged[key] = default_gen_config[key]
+    return merged
+
+
+def extract_request_sampling_values(request: Any) -> dict[str, Any]:
+    """Extract non-None GenerationConfig fields present on the request."""
+    values: dict[str, Any] = {}
+    for field in dataclasses.fields(GenerationConfig):
+        if not hasattr(request, field.name):
+            continue
+        value = getattr(request, field.name)
+        if value is not None:
+            values[field.name] = value
+    return values
+
+
+def build_generation_config(
+    request: Any,
+    default_gen_config: dict[str, Any],
+    *,
+    max_new_tokens: int | None = None,
+    **extra_kwargs: Any,
+) -> GenerationConfig:
+    """Build ``GenerationConfig`` from merged sampling defaults and request
+    values."""
+    request_values = extract_request_sampling_values(request)
+    merged = merge_sampling_params(request_values, default_gen_config)
+    merged.pop('max_new_tokens', None)
+    merged.pop('do_sample', None)
+    return GenerationConfig(
+        max_new_tokens=max_new_tokens,
+        do_sample=True,
+        **merged,
+        **extra_kwargs,
+    )
diff --git a/lmdeploy/serve/openai/api_server.py b/lmdeploy/serve/openai/api_server.py
index e8a3ca6ecc..abdc7a320f 100644
--- a/lmdeploy/serve/openai/api_server.py
+++ b/lmdeploy/serve/openai/api_server.py
@@ -47,6 +47,10 @@
 )
 from lmdeploy.serve.anthropic import create_anthropic_router
 from lmdeploy.serve.core import AsyncEngine, EngineHealthMonitor
+from lmdeploy.serve.core.generation_config import (
+    build_generation_config,
+    resolve_default_gen_config,
+)
 from lmdeploy.serve.openai.protocol import (
     AbortRequest,
     ChatCompletionRequest,
@@ -110,6 +114,7 @@ class VariableInterface:
     allow_terminate_by_client: bool = False
     enable_abort_handling: bool = False
     response_parser_cls: type[ResponseParser] | None = None
+    default_gen_config: dict = {}
 
     @classmethod
     def create_session(cls, user_session_id: int | None = None) -> Session:
@@ -147,6 +152,19 @@ def get_engine_config(cls):
         return cls.async_engine.backend_config
 
 
+def _build_serving_generation_config(request, **extra_kwargs) -> GenerationConfig:
+    """Build ``GenerationConfig`` with server and request sampling merge."""
+    max_new_tokens = getattr(request, 'max_completion_tokens', None)
+    if max_new_tokens is None:
+        max_new_tokens = getattr(request, 'max_tokens', None)
+    return build_generation_config(
+        request,
+        VariableInterface.default_gen_config,
+        max_new_tokens=max_new_tokens,
+        **extra_kwargs,
+    )
+
+
 async def _with_request_cleanup(generator, result_generators, sessions):
     """Yield from an API generator and cleanup when the HTTP task exits."""
     session_mgr = VariableInterface.get_session_manager()
@@ -486,14 +504,9 @@ async def chat_completions_v1(request: ChatCompletionRequest, raw_request: Reque
     # (e.g. GPT-OSS clears response_format and injects the schema into messages)
     request = response_parser.request
 
-    gen_config = GenerationConfig(
-        max_new_tokens=request.max_completion_tokens,
-        do_sample=True,
+    gen_config = _build_serving_generation_config(
+        request,
         logprobs=gen_logprobs,
-        top_k=request.top_k,
-        top_p=request.top_p,
-        temperature=request.temperature,
-        repetition_penalty=request.repetition_penalty,
         ignore_eos=request.ignore_eos,
         stop_words=request.stop,
         include_stop_str_in_output=request.include_stop_str_in_output,
@@ -501,7 +514,6 @@ async def chat_completions_v1(request: ChatCompletionRequest, raw_request: Reque
         response_format=request.response_format,
         logits_processors=logits_processors,
         min_new_tokens=request.min_new_tokens,
-        min_p=request.min_p,
         random_seed=random_seed,
         spaces_between_special_tokens=request.spaces_between_special_tokens,
         migration_request=migration_request,
@@ -828,20 +840,13 @@ async def completions_v1(request: CompletionRequest, raw_request: Request = None
     if isinstance(request.stop, str):
         request.stop = [request.stop]
     random_seed = request.seed if request.seed is not None else None
-    max_new_tokens = (request.max_completion_tokens if request.max_completion_tokens else request.max_tokens)
 
-    gen_config = GenerationConfig(
-        max_new_tokens=max_new_tokens,
-        do_sample=True,
+    gen_config = _build_serving_generation_config(
+        request,
         logprobs=request.logprobs,
-        top_k=request.top_k,
-        top_p=request.top_p,
-        temperature=request.temperature,
-        repetition_penalty=request.repetition_penalty,
         ignore_eos=request.ignore_eos,
         stop_words=request.stop,
         skip_special_tokens=request.skip_special_tokens,
-        min_p=request.min_p,
         random_seed=random_seed,
         spaces_between_special_tokens=request.spaces_between_special_tokens,
         migration_request=migration_request,
@@ -1012,15 +1017,9 @@ async def generate(request: GenerateReqInput, raw_request: Request = None):
         prompt = [dict(role='user', content=[text_input] + image_input)]
         input_ids = None
 
-    gen_config = GenerationConfig(
-        max_new_tokens=request.max_tokens,
-        do_sample=True,
+    gen_config = _build_serving_generation_config(
+        request,
         logprobs=1 if request.return_logprob else None,
-        top_k=request.top_k,
-        top_p=request.top_p,
-        min_p=request.min_p,
-        temperature=request.temperature,
-        repetition_penalty=request.repetition_penalty,
         ignore_eos=request.ignore_eos,
         stop_words=request.stop,
         stop_token_ids=request.stop_token_ids,
@@ -1546,6 +1545,7 @@ def serve(model_path: str,
           allow_terminate_by_client: bool = False,
           enable_abort_handling: bool = False,
           speculative_config: SpeculativeConfig | None = None,
+          generation_config: str = 'auto',
           **kwargs):
     """An example to perform model inference through the command line
     interface.
@@ -1606,6 +1606,12 @@ def serve(model_path: str,
     VariableInterface.allow_terminate_by_client = allow_terminate_by_client
     VariableInterface.enable_abort_handling = enable_abort_handling
 
+    VariableInterface.default_gen_config = resolve_default_gen_config(
+        generation_config,
+        model_path,
+        trust_remote_code,
+    )
+
     ssl_keyfile, ssl_certfile, http_or_https = None, None, 'http'
     if ssl:
         ssl_keyfile = os.environ['SSL_KEYFILE']
diff --git a/lmdeploy/serve/openai/protocol.py b/lmdeploy/serve/openai/protocol.py
index 675cbf5103..40162faf15 100644
--- a/lmdeploy/serve/openai/protocol.py
+++ b/lmdeploy/serve/openai/protocol.py
@@ -144,8 +144,8 @@ class ChatCompletionRequest(BaseModel):
     model: str
 
     messages: str | list[dict[str, Any]] = Field(examples=[[{'role': 'user', 'content': 'hi'}]])
-    temperature: float | None = 0.7
-    top_p: float | None = 1.0
+    temperature: float | None = None
+    top_p: float | None = None
     tools: list[Tool] | None = Field(default=None, examples=[None])
     tool_choice: ToolChoice | AllowedToolChoice | Literal[
         'auto', 'required', 'none'] = Field(default='auto', examples=['none'])
@@ -176,17 +176,17 @@ class ChatCompletionRequest(BaseModel):
     response_format: ResponseFormat | None = Field(default=None, examples=[None])
     # additional argument of lmdeploy
     do_preprocess: bool | None = True
-    repetition_penalty: float | None = 1.0
+    repetition_penalty: float | None = None
     repetition_ngram_size: int = Field(default=0, ge=0)
     repetition_ngram_threshold: int = Field(default=0, ge=0)
     session_id: int | None = -1
     ignore_eos: bool | None = False
     skip_special_tokens: bool | None = True
     spaces_between_special_tokens: bool | None = True
-    top_k: int | None = 40
+    top_k: int | None = None
     seed: int | None = None
     min_new_tokens: int | None = Field(default=None, examples=[None])
-    min_p: float = 0.0
+    min_p: float | None = None
     enable_thinking: bool | None = None  # will be deprecated in the future
     return_token_ids: bool | None = False
     return_logprob: bool | None = False
@@ -352,7 +352,7 @@ class CompletionRequest(BaseModel):
     model: str
     prompt: str | list[Any]
     suffix: str | None = None
-    temperature: float | None = 0.7
+    temperature: float | None = None
     n: int | None = 1
     logprobs: int | None = None
     max_completion_tokens: int | None = Field(
@@ -362,29 +362,29 @@ class CompletionRequest(BaseModel):
                      'including visible output tokens and reasoning tokens'),
     )
     max_tokens: int | None = Field(
-        default=16,
-        examples=[16],
+        default=None,
+        examples=[None],
         deprecated='max_tokens is deprecated in favor of the max_completion_tokens field',
     )
     stop: str | list[str] | None = Field(default=None, examples=[None])
     stream: bool | None = False
     stream_options: StreamOptions | None = Field(default=None, examples=[None])
-    top_p: float | None = 1.0
+    top_p: float | None = None
     echo: bool | None = False
     presence_penalty: float | None = 0.0
     frequency_penalty: float | None = 0.0
     user: str | None = None
     # additional argument of lmdeploy
-    repetition_penalty: float | None = 1.0
+    repetition_penalty: float | None = None
     repetition_ngram_size: int = Field(default=0, ge=0)
     repetition_ngram_threshold: int = Field(default=0, ge=0)
     session_id: int | None = -1
     ignore_eos: bool | None = False
     skip_special_tokens: bool | None = True
     spaces_between_special_tokens: bool | None = True
-    top_k: int | None = 40  # for opencompass
+    top_k: int | None = None  # for opencompass
     seed: int | None = None
-    min_p: float = 0.0
+    min_p: float | None = None
 
 
 class CompletionResponseChoice(BaseModel):
@@ -550,7 +550,7 @@ class GenerateReqInput(BaseModel):
     stop_token_ids: list[int] | None = None
     stream: bool | None = False
     temperature: float = 1.0
-    repetition_penalty: float | None = 1.0
+    repetition_penalty: float | None = None
     ignore_eos: bool | None = False
     top_p: float = 1.0
     top_k: int = 0
diff --git a/lmdeploy/serve/openai/responses/protocol.py b/lmdeploy/serve/openai/responses/protocol.py
index ed08f16202..d02d220df7 100644
--- a/lmdeploy/serve/openai/responses/protocol.py
+++ b/lmdeploy/serve/openai/responses/protocol.py
@@ -82,10 +82,10 @@ class ResponsesRequest(BaseModel):
     presence_penalty: float | None = None
     frequency_penalty: float | None = None
     repetition_penalty: float | None = None
-    top_k: int | None = 40
+    top_k: int | None = None
     stop: str | list[str] | None = None
     seed: int | None = None
-    min_p: float = 0.0
+    min_p: float | None = None
     ignore_eos: bool | None = False
     skip_special_tokens: bool | None = True
     include_stop_str_in_output: bool | None = False
diff --git a/lmdeploy/serve/openai/responses/request.py b/lmdeploy/serve/openai/responses/request.py
index 2db1000532..50d6927139 100644
--- a/lmdeploy/serve/openai/responses/request.py
+++ b/lmdeploy/serve/openai/responses/request.py
@@ -9,6 +9,7 @@
 from fastapi.responses import JSONResponse
 
 from lmdeploy.messages import GenerationConfig
+from lmdeploy.serve.core.generation_config import build_generation_config
 from lmdeploy.serve.openai.protocol import Tool, ToolChoice, ToolChoiceFuncName
 from lmdeploy.serve.openai.responses.protocol import ResponsesRequest
 from lmdeploy.utils import get_logger
@@ -264,20 +265,19 @@ def _response_format_from_text(text: Any) -> dict[str, Any] | None:
     raise ValueError(f'Unsupported text.format type: {format_type!r}.')
 
 
-def to_generation_config(request: ResponsesRequest) -> GenerationConfig:
+def to_generation_config(
+    request: ResponsesRequest,
+    default_gen_config: dict | None = None,
+) -> GenerationConfig:
     stop_words = [request.stop] if isinstance(request.stop, str) else request.stop
-    return GenerationConfig(
+    return build_generation_config(
+        request,
+        default_gen_config or {},
         max_new_tokens=request.max_output_tokens,
-        do_sample=True,
-        top_k=40 if request.top_k is None else request.top_k,
-        top_p=1.0 if request.top_p is None else request.top_p,
-        temperature=1.0 if request.temperature is None else request.temperature,
         stop_words=stop_words,
         ignore_eos=request.ignore_eos,
         skip_special_tokens=request.skip_special_tokens,
         include_stop_str_in_output=request.include_stop_str_in_output,
         response_format=_response_format_from_text(request.text),
-        min_p=request.min_p,
         random_seed=request.seed,
-        repetition_penalty=1.0 if request.repetition_penalty is None else request.repetition_penalty,
     )
diff --git a/lmdeploy/serve/openai/responses/serving.py b/lmdeploy/serve/openai/responses/serving.py
index 2837e483c5..abcac88908 100644
--- a/lmdeploy/serve/openai/responses/serving.py
+++ b/lmdeploy/serve/openai/responses/serving.py
@@ -97,7 +97,10 @@ async def create_response(self, request: ResponsesRequest, raw_request: Request)
         except ValueError as err:
             return error_response(HTTPStatus.BAD_REQUEST, str(err), param='input')
         try:
-            gen_config = to_generation_config(request)
+            gen_config = to_generation_config(
+                request,
+                default_gen_config=self.server_context.default_gen_config,
+            )
         except ValueError as err:
             return error_response(HTTPStatus.BAD_REQUEST, str(err), param='text')
         try:
diff --git a/lmdeploy/serve/openai/serving_chat_completion.py b/lmdeploy/serve/openai/serving_chat_completion.py
index 362f0bf9e5..8c44e5badd 100644
--- a/lmdeploy/serve/openai/serving_chat_completion.py
+++ b/lmdeploy/serve/openai/serving_chat_completion.py
@@ -1,12 +1,23 @@
 # Copyright (c) OpenMMLab. All rights reserved.
 from typing import TYPE_CHECKING
 
+from lmdeploy.serve.core.generation_config import build_generation_config
+
 from .protocol import ChatCompletionRequest
 
 if TYPE_CHECKING:
     from .api_server import VariableInterface
 
 
+def _effective_sampling(request: ChatCompletionRequest, server_context: 'VariableInterface') -> dict:
+    gen = build_generation_config(request, server_context.default_gen_config)
+    return {
+        'temperature': gen.temperature,
+        'top_p': gen.top_p,
+        'top_k': gen.top_k,
+    }
+
+
 def check_request(request: ChatCompletionRequest, server_context: 'VariableInterface') -> str:
     engine_config = server_context.get_engine_config()
     session_manager = server_context.get_session_manager()
@@ -32,15 +43,17 @@ def check_request(request: ChatCompletionRequest, server_context: 'VariableInter
     if session_manager.has(request.session_id):
         return f'The session_id {request.session_id!r} is occupied.'
 
+    sampling = _effective_sampling(request, server_context)
+
     # check sampling settings
     if request.n <= 0:
         return f'The n {request.n!r} must be a positive int.'
-    if not (0 < request.top_p <= 1):
-        return f'The top_p {request.top_p!r} must be in (0, 1].'
-    if request.top_k < 0:
-        return f'The top_k {request.top_k!r} cannot be a negative integer.'
-    if not (0 <= request.temperature <= 2):
-        return f'The temperature {request.temperature!r} must be in [0, 2]'
+    if not (0 < sampling['top_p'] <= 1):
+        return f'The top_p {sampling["top_p"]!r} must be in (0, 1].'
+    if sampling['top_k'] < 0:
+        return f'The top_k {sampling["top_k"]!r} cannot be a negative integer.'
+    if not (0 <= sampling['temperature'] <= 2):
+        return f'The temperature {sampling["temperature"]!r} must be in [0, 2]'
 
     # Validate input_ids and image_data constraints.
     # messages has higher priority. input_ids and image_data are only used when
diff --git a/lmdeploy/serve/openai/serving_completion.py b/lmdeploy/serve/openai/serving_completion.py
index 759972db36..ca96f8789d 100644
--- a/lmdeploy/serve/openai/serving_completion.py
+++ b/lmdeploy/serve/openai/serving_completion.py
@@ -1,12 +1,23 @@
 # Copyright (c) OpenMMLab. All rights reserved.
 from typing import TYPE_CHECKING
 
+from lmdeploy.serve.core.generation_config import build_generation_config
+
 from .protocol import CompletionRequest
 
 if TYPE_CHECKING:
     from .api_server import VariableInterface
 
 
+def _effective_sampling(request: CompletionRequest, server_context: 'VariableInterface') -> dict:
+    gen = build_generation_config(request, server_context.default_gen_config)
+    return {
+        'temperature': gen.temperature,
+        'top_p': gen.top_p,
+        'top_k': gen.top_k,
+    }
+
+
 def check_request(request: CompletionRequest, server_context: 'VariableInterface') -> str:
     engine_config = server_context.get_engine_config()
     session_manager = server_context.get_session_manager()
@@ -24,14 +35,16 @@ def check_request(request: CompletionRequest, server_context: 'VariableInterface
     if session_manager.has(request.session_id):
         return f'The session_id {request.session_id!r} is occupied.'
 
+    sampling = _effective_sampling(request, server_context)
+
     # check sampling settings
     if request.n <= 0:
         return f'The n {request.n!r} must be a positive int.'
-    if not (0 < request.top_p <= 1):
-        return f'The top_p {request.top_p!r} must be in (0, 1].'
-    if request.top_k < 0:
-        return f'The top_k {request.top_k!r} cannot be a negative integer.'
-    if not (0 <= request.temperature <= 2):
-        return f'The temperature {request.temperature!r} must be in [0, 2]'
+    if not (0 < sampling['top_p'] <= 1):
+        return f'The top_p {sampling["top_p"]!r} must be in (0, 1].'
+    if sampling['top_k'] < 0:
+        return f'The top_k {sampling["top_k"]!r} cannot be a negative integer.'
+    if not (0 <= sampling['temperature'] <= 2):
+        return f'The temperature {sampling["temperature"]!r} must be in [0, 2]'
 
     return ''
diff --git a/tests/test_lmdeploy/serve/test_generation_config.py b/tests/test_lmdeploy/serve/test_generation_config.py
new file mode 100644
index 0000000000..8946ef8a61
--- /dev/null
+++ b/tests/test_lmdeploy/serve/test_generation_config.py
@@ -0,0 +1,86 @@
+# Copyright (c) OpenMMLab. All rights reserved.
+from unittest.mock import patch
+
+from lmdeploy.messages import GenerationConfig
+from lmdeploy.serve.core.generation_config import (
+    build_generation_config,
+    extract_request_sampling_values,
+    merge_sampling_params,
+    resolve_default_gen_config,
+)
+from lmdeploy.serve.openai.protocol import ChatCompletionRequest, CompletionRequest
+
+_DEFAULTS = GenerationConfig()
+
+
+def test_merge_sampling_params_priority():
+    merged = merge_sampling_params(
+        {'temperature': 0.2},
+        {'temperature': 0.5, 'top_k': 10},
+    )
+    assert merged == {'temperature': 0.2, 'top_k': 10}
+
+
+def test_merge_sampling_params_uses_server_defaults():
+    merged = merge_sampling_params({}, {'temperature': 0.5})
+    assert merged == {'temperature': 0.5}
+
+
+def test_extract_request_sampling_values_only_non_null():
+    request = ChatCompletionRequest(model='test', messages='hi', temperature=0.3)
+    values = extract_request_sampling_values(request)
+    assert values == {'temperature': 0.3}
+
+
+def test_build_generation_config_from_merged_values():
+    request = ChatCompletionRequest(model='test', messages='hi', temperature=0.2)
+    gen_config = build_generation_config(
+        request,
+        {'top_k': 5},
+        max_new_tokens=32,
+    )
+    assert gen_config.temperature == 0.2
+    assert gen_config.top_k == 5
+    assert gen_config.max_new_tokens == 32
+    assert gen_config.do_sample is True
+
+
+def test_build_generation_config_max_new_tokens_defaults_to_none():
+    request = CompletionRequest(model='test', prompt='hello')
+    gen_config = build_generation_config(request, {})
+    assert gen_config.max_new_tokens is None
+
+
+def test_build_generation_config_uses_generation_config_defaults():
+    request = CompletionRequest(model='test', prompt='hello')
+    gen_config = build_generation_config(request, {})
+    assert gen_config.temperature == _DEFAULTS.temperature
+    assert gen_config.top_k == _DEFAULTS.top_k
+
+
+@patch('lmdeploy.serve.core.generation_config._load_hf_generation_config')
+def test_resolve_default_gen_config_auto(mock_load):
+    mock_load.return_value = {
+        'temperature': 0.6,
+        'top_p': 0.8,
+        'max_new_tokens': 2048,
+    }
+    config = resolve_default_gen_config('auto', '/fake/model', False)
+    assert config == {
+        'temperature': 0.6,
+        'top_p': 0.8,
+        'max_new_tokens': 2048,
+    }
+    mock_load.assert_called_once_with('/fake/model', False)
+
+
+def test_resolve_default_gen_config_lmdeploy():
+    config = resolve_default_gen_config('lmdeploy', '/fake/model', False)
+    assert config == {}
+
+
+def test_completion_request_sampling_merge():
+    request = CompletionRequest(model='test', prompt='hello')
+    gen_config = build_generation_config(request, {'temperature': 0.9})
+    assert gen_config.temperature == 0.9
+    assert gen_config.top_k == _DEFAULTS.top_k