diff --git a/chromadb/test/ef/test_ef.py b/chromadb/test/ef/test_ef.py
index 264284ecebe..186d8b6ff19 100644
--- a/chromadb/test/ef/test_ef.py
+++ b/chromadb/test/ef/test_ef.py
@@ -39,6 +39,7 @@ def test_get_builtins_holds() -> None:
         "JinaEmbeddingFunction",
         "MistralEmbeddingFunction",
         "MorphEmbeddingFunction",
+        "NomicEmbeddingFunction",
         "ONNXMiniLM_L6_V2",
         "OllamaEmbeddingFunction",
         "OpenAIEmbeddingFunction",
diff --git a/chromadb/utils/embedding_functions/__init__.py b/chromadb/utils/embedding_functions/__init__.py
index f2ca5ecb9a3..2622b6f0e5e 100644
--- a/chromadb/utils/embedding_functions/__init__.py
+++ b/chromadb/utils/embedding_functions/__init__.py
@@ -68,6 +68,10 @@
 from chromadb.utils.embedding_functions.morph_embedding_function import (
     MorphEmbeddingFunction,
 )
+from chromadb.utils.embedding_functions.nomic_embedding_function import (
+    NomicEmbeddingFunction,
+    NomicQueryConfig,
+)
 from chromadb.utils.embedding_functions.huggingface_sparse_embedding_function import (
     HuggingFaceSparseEmbeddingFunction,
 )
@@ -103,6 +107,7 @@
     "JinaEmbeddingFunction",
     "MistralEmbeddingFunction",
     "MorphEmbeddingFunction",
+    "NomicEmbeddingFunction",
     "VoyageAIEmbeddingFunction",
     "ONNXMiniLM_L6_V2",
     "OpenCLIPEmbeddingFunction",
@@ -142,6 +147,7 @@ def get_builtins() -> Set[str]:
     "jina": JinaEmbeddingFunction,
     "mistral": MistralEmbeddingFunction,
     "morph": MorphEmbeddingFunction,
+    "nomic": NomicEmbeddingFunction,
     "voyageai": VoyageAIEmbeddingFunction,
     "onnx_mini_lm_l6_v2": ONNXMiniLM_L6_V2,
     "open_clip": OpenCLIPEmbeddingFunction,
@@ -265,6 +271,8 @@ def config_to_embedding_function(config: Dict[str, Any]) -> EmbeddingFunction:
     "JinaQueryConfig",
     "MistralEmbeddingFunction",
     "MorphEmbeddingFunction",
+    "NomicEmbeddingFunction",
+    "NomicQueryConfig",
     "VoyageAIEmbeddingFunction",
     "ONNXMiniLM_L6_V2",
     "OpenCLIPEmbeddingFunction",
diff --git a/chromadb/utils/embedding_functions/nomic_embedding_function.py b/chromadb/utils/embedding_functions/nomic_embedding_function.py
new file mode 100644
index 00000000000..c65c5864d0e
--- /dev/null
+++ b/chromadb/utils/embedding_functions/nomic_embedding_function.py
@@ -0,0 +1,129 @@
+from chromadb.api.types import (
+    Embeddings,
+    Documents,
+    EmbeddingFunction,
+    Space,
+)
+from chromadb.utils.embedding_functions.schemas import validate_config_schema
+from typing import List, Dict, Any, TypedDict, Optional
+import os
+import numpy as np
+
+
+class NomicQueryConfig(TypedDict):
+    task_type: str
+
+
+class NomicEmbeddingFunction(EmbeddingFunction[Documents]):
+    """
+    This class is used to get embeddings for a list of texts using the Nomic API.
+    """
+
+    def __init__(
+        self,
+        model: str,
+        task_type: str,
+        query_config: Optional[NomicQueryConfig],
+        api_key_env_var: str = "NOMIC_API_KEY",
+    ):
+        """
+        Initialize the NomicEmbeddingFunction.
+
+        Args:
+            model (str): The name of the model to use for text embeddings.
+            task_type (str): The type of task to embed with. See reference https://docs.nomic.ai/platform/embeddings-and-retrieval/text-embedding#embedding-task-types
+            query_config (Optional[NomicQueryConfig]): The configuration for setting task type for queries
+            api_key_env_var (str): The environment variable name for the Nomic API key. Defaults to "NOMIC_API_KEY".
+
+            Supported task types: search_document, search_query, classification, clustering
+        """
+        try:
+            from nomic import embed
+        except ImportError:
+            raise ValueError(
+                "The nomic python package is not installed. Please install it with `pip install nomic`"
+            )
+
+        self.model = model
+        self.task_type = task_type
+        self.api_key_env_var = api_key_env_var
+        self.api_key = os.getenv(api_key_env_var)
+        self.query_config = query_config
+        if not self.api_key:
+            raise ValueError(f"The {api_key_env_var} environment variable is not set.")
+        self.embed = embed
+
+    def __call__(self, input: Documents) -> Embeddings:
+        if not all(isinstance(item, str) for item in input):
+            raise ValueError("Nomic only supports text documents, not images")
+        output = self.embed.text(
+            model=self.model,
+            texts=input,
+            task_type=self.task_type,
+        )
+        return [np.array(data.embedding) for data in output.data]
+
+    def embed_query(self, input: Documents) -> Embeddings:
+        if not all(isinstance(item, str) for item in input):
+            raise ValueError("Nomic only supports text queries, not images")
+
+        task_type = (
+            self.query_config.get("task_type") if self.query_config else self.task_type
+        )
+        output = self.embed.text(
+            model=self.model,
+            texts=input,
+            task_type=task_type,
+        )
+        return [np.array(data.embedding) for data in output.data]
+
+    @staticmethod
+    def name() -> str:
+        return "nomic"
+
+    def default_space(self) -> Space:
+        return "cosine"
+
+    def supported_spaces(self) -> List[Space]:
+        return ["cosine", "l2", "ip"]
+
+    @staticmethod
+    def build_from_config(config: Dict[str, Any]) -> "EmbeddingFunction[Documents]":
+        model = config.get("model")
+        api_key_env_var = config.get("api_key_env_var")
+        task_type = config.get("task_type")
+        query_config = config.get("query_config")
+        if model is None or api_key_env_var is None or task_type is None:
+            assert False, "This code should not be reached"  # this is for type checking
+        return NomicEmbeddingFunction(
+            model=model,
+            api_key_env_var=api_key_env_var,
+            task_type=task_type,
+            query_config=query_config,
+        )
+
+    def get_config(self) -> Dict[str, Any]:
+        return {
+            "model": self.model,
+            "api_key_env_var": self.api_key_env_var,
+            "task_type": self.task_type,
+            "query_config": self.query_config,
+        }
+
+    def validate_config_update(
+        self, old_config: Dict[str, Any], new_config: Dict[str, Any]
+    ) -> None:
+        if "model" in new_config:
+            raise ValueError(
+                "The model cannot be changed after the embedding function has been initialized."
+            )
+
+    @staticmethod
+    def validate_config(config: Dict[str, Any]) -> None:
+        """
+        Validate the configuration using the JSON schema.
+
+        Args:
+            config: Configuration to validate
+        """
+        validate_config_schema(config, "nomic")
diff --git a/schemas/embedding_functions/nomic.json b/schemas/embedding_functions/nomic.json
new file mode 100644
index 00000000000..d20722a9d48
--- /dev/null
+++ b/schemas/embedding_functions/nomic.json
@@ -0,0 +1,21 @@
+{
+    "$schema": "http://json-schema.org/draft-07/schema#",
+    "title": "Nomic Embedding Function Schema",
+    "description": "Schema for the Nomic embedding function configuration",
+    "version": "1.0.0",
+    "type": "object",
+    "properties": {
+        "model": {
+            "type": "string",
+            "description": "Parameter model for the Nomic embedding function"
+        },
+        "api_key_env_var": {
+            "type": "string",
+            "description": "Parameter api_key_env_var for the Nomic embedding function"
+        },
+        "task_type": {
+            "type": "string",
+            "description": "Parameter task_type for the Nomic embedding function"
+        }
+    }
+}