diff --git a/atroposlib/envs/base.py b/atroposlib/envs/base.py
index 81569f0d..75ed08e2 100644
--- a/atroposlib/envs/base.py
+++ b/atroposlib/envs/base.py
@@ -1654,20 +1654,29 @@ class BaseEnv(ABC):
                     cli_passed_flags, openai_full_prefix
                 )  # CLI args
                 yaml_oai_config = yaml_config.get(OPENAI_NAMESPACE, {})
-                if isinstance(default_server_configs, ServerBaseline) and (
+                
+                # Auto-convert ServerBaseline to APIServerConfig when CLI/YAML overrides are provided
+                # This allows any environment to use --openai.* CLI args without modifying config_init
+                # Use a new variable to avoid UnboundLocalError from closure scoping
+                effective_server_configs = default_server_configs
+                if isinstance(effective_server_configs, ServerBaseline) and (
                     oai_cli_passed_args or yaml_oai_config
                 ):
-                    raise ValueError(
-                        "ServerBaseline is not compatible with OpenAI-namespaced CLI arguments. Please edit `config_init` directly or use APIServerConfig."  # noqa: E501
+                    # Convert ServerBaseline to APIServerConfig, preserving common fields
+                    baseline_dict = effective_server_configs.model_dump()
+                    effective_server_configs = APIServerConfig(**baseline_dict)
+                    logger.info(
+                        "Auto-converted ServerBaseline to APIServerConfig for CLI/YAML overrides"
                     )
+                
                 if (
-                    isinstance(default_server_configs, list)
-                    and len(default_server_configs) == 1
+                    isinstance(effective_server_configs, list)
+                    and len(effective_server_configs) == 1
                 ):
                     # can't use the same var name because it shadows the class variable and we get an error
-                    default_openai_config_ = default_server_configs[0]
+                    default_openai_config_ = effective_server_configs[0]
                 else:
-                    default_openai_config_ = default_server_configs
+                    default_openai_config_ = effective_server_configs
                 if isinstance(yaml_oai_config, list) and len(yaml_oai_config) == 1:
                     yaml_oai_config = yaml_oai_config[0]
                 if isinstance(default_openai_config_, APIServerConfig) and isinstance(
@@ -1717,7 +1726,7 @@ class BaseEnv(ABC):
                 # Determine the final server_configs, handling single, multiple servers, and overrides.
 
                 openai_configs = resolve_openai_configs(
-                    default_server_configs=default_server_configs,
+                    default_server_configs=effective_server_configs,
                     openai_config_dict=openai_config_dict,
                     yaml_config=yaml_config,
                     cli_passed_flags=cli_passed_flags,
diff --git a/environments/math_server_zero.py b/environments/math_server_zero.py
index 0d6c140c..1432ab4d 100644
--- a/environments/math_server_zero.py
+++ b/environments/math_server_zero.py
@@ -18,7 +18,6 @@ from pydantic import Field
 from tqdm.asyncio import tqdm_asyncio
 
 from atroposlib.envs.base import (
-    APIServerConfig,
     BaseEnv,
     BaseEnvConfig,
     EvalHandlingEnum,
@@ -120,7 +119,7 @@ class MathEnv(BaseEnv):
     def __init__(
         self,
         config: RSConfig,
-        server_configs: APIServerConfig | ServerBaseline,
+        server_configs: ServerBaseline,
         slurm=True,
         testing=False,
     ):
@@ -138,7 +137,7 @@ class MathEnv(BaseEnv):
         self.iter = 0
 
     @classmethod
-    def config_init(cls) -> Tuple[RSConfig, APIServerConfig]:
+    def config_init(cls) -> Tuple[RSConfig, ServerBaseline]:
         env_config = RSConfig(
             tokenizer_name="Qwen/Qwen2.5-7B",
             group_size=16,
@@ -153,11 +152,10 @@ class MathEnv(BaseEnv):
             eval_limit_ratio=0.1,
             max_num_workers_per_node=24,
         )
-        server_configs = APIServerConfig(
+        server_configs = ServerBaseline(
             model_name="Qwen/Qwen2.5-7B",
             num_requests_for_eval=256,  # since evaling only on one...
             server_type="vllm",
-            base_url="",  # Override via CLI: --openai.base_url
         )
 
         return env_config, server_configs