diff --git a/libs/partners/anthropic/langchain_anthropic/chat_models.py b/libs/partners/anthropic/langchain_anthropic/chat_models.py
index 512ffb81aa1..6456167528f 100644
--- a/libs/partners/anthropic/langchain_anthropic/chat_models.py
+++ b/libs/partners/anthropic/langchain_anthropic/chat_models.py
@@ -89,34 +89,9 @@ def _get_default_model_profile(model_name: str) -> ModelProfile:
     return {}
 
 
-_MODEL_DEFAULT_MAX_OUTPUT_TOKENS: Final[dict[str, int]] = {
-    # Listed old to new
-    "claude-3-haiku": 4096,  # Claude Haiku 3
-    "claude-3-5-haiku": 8192,  # Claude Haiku 3.5
-    "claude-3-7-sonnet": 64000,  # Claude Sonnet 3.7
-    "claude-sonnet-4": 64000,  # Claude Sonnet 4
-    "claude-opus-4": 32000,  # Claude Opus 4
-    "claude-opus-4-1": 32000,  # Claude Opus 4.1
-    "claude-sonnet-4-5": 64000,  # Claude Sonnet 4.5
-    "claude-haiku-4-5": 64000,  # Claude Haiku 4.5
-}
 _FALLBACK_MAX_OUTPUT_TOKENS: Final[int] = 4096
 
 
-def _default_max_tokens_for(model: str | None) -> int:
-    """Return the default max output tokens for an Anthropic model (with fallback).
-
-    See the Claude docs for [Max Tokens limits](https://platform.claude.com/docs/en/about-claude/models/overview#model-comparison-table).
-    """
-    if not model:
-        return _FALLBACK_MAX_OUTPUT_TOKENS
-
-    parts = model.split("-")
-    family = "-".join(parts[:-1]) if len(parts) > 1 else model
-
-    return _MODEL_DEFAULT_MAX_OUTPUT_TOKENS.get(family, _FALLBACK_MAX_OUTPUT_TOKENS)
-
-
 class AnthropicTool(TypedDict):
     """Anthropic tool definition."""
 
@@ -1869,10 +1844,13 @@ class ChatAnthropic(BaseChatModel):
     @model_validator(mode="before")
     @classmethod
     def set_default_max_tokens(cls, values: dict[str, Any]) -> Any:
-        """Set default `max_tokens`."""
+        """Set default `max_tokens` from model profile with fallback."""
         if values.get("max_tokens") is None:
             model = values.get("model") or values.get("model_name")
-            values["max_tokens"] = _default_max_tokens_for(model)
+            profile = _get_default_model_profile(model) if model else {}
+            values["max_tokens"] = profile.get(
+                "max_output_tokens", _FALLBACK_MAX_OUTPUT_TOKENS
+            )
         return values
 
     @model_validator(mode="before")