diff --git a/poetry.lock b/poetry.lock
index 1631e34..a093539 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
 
 [[package]]
 name = "aiohttp"
@@ -136,6 +136,28 @@ files = [
 [package.dependencies]
 typing-extensions = {version = ">=4.0.0", markers = "python_version < \"3.9\""}
 
+[[package]]
+name = "anyio"
+version = "4.3.0"
+description = "High level compatibility layer for multiple asynchronous event loop implementations"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "anyio-4.3.0-py3-none-any.whl", hash = "sha256:048e05d0f6caeed70d731f3db756d35dcc1f35747c8c403364a8332c630441b8"},
+    {file = "anyio-4.3.0.tar.gz", hash = "sha256:f75253795a87df48568485fd18cdd2a3fa5c4f7c5be8e5e36637733fce06fed6"},
+]
+
+[package.dependencies]
+exceptiongroup = {version = ">=1.0.2", markers = "python_version < \"3.11\""}
+idna = ">=2.8"
+sniffio = ">=1.1"
+typing-extensions = {version = ">=4.1", markers = "python_version < \"3.11\""}
+
+[package.extras]
+doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
+test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
+trio = ["trio (>=0.23)"]
+
 [[package]]
 name = "async-timeout"
 version = "4.0.3"
@@ -429,6 +451,17 @@ files = [
 [package.extras]
 graph = ["objgraph (>=1.7.2)"]
 
+[[package]]
+name = "distro"
+version = "1.9.0"
+description = "Distro - an OS platform information API"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "distro-1.9.0-py3-none-any.whl", hash = "sha256:7bffd925d65168f85027d8da9af6bddab658135b840670a223589bc0c8ef02b2"},
+    {file = "distro-1.9.0.tar.gz", hash = "sha256:2fa77c6fd8940f116ee1d6b94a2f90b13b5ea8d019b98bc8bafdcabcdd9bdbed"},
+]
+
 [[package]]
 name = "eval-type-backport"
 version = "0.1.3"
@@ -443,6 +476,20 @@ files = [
 [package.extras]
 tests = ["pytest"]
 
+[[package]]
+name = "exceptiongroup"
+version = "1.2.0"
+description = "Backport of PEP 654 (exception groups)"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "exceptiongroup-1.2.0-py3-none-any.whl", hash = "sha256:4bfd3996ac73b41e9b9628b04e079f193850720ea5945fc96a08633c66912f14"},
+    {file = "exceptiongroup-1.2.0.tar.gz", hash = "sha256:91f5c769735f051a4290d52edd0858999b57e5876e9f85937691bd4c9fa3ed68"},
+]
+
+[package.extras]
+test = ["pytest (>=6)"]
+
 [[package]]
 name = "filelock"
 version = "3.13.1"
@@ -630,6 +677,62 @@ files = [
 unidic = ["unidic"]
 unidic-lite = ["unidic-lite"]
 
+[[package]]
+name = "h11"
+version = "0.14.0"
+description = "A pure-Python, bring-your-own-I/O implementation of HTTP/1.1"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "h11-0.14.0-py3-none-any.whl", hash = "sha256:e3fe4ac4b851c468cc8363d500db52c2ead036020723024a109d37346efaa761"},
+    {file = "h11-0.14.0.tar.gz", hash = "sha256:8f19fbbe99e72420ff35c00b27a34cb9937e902a8b810e2c88300c6f0a3b699d"},
+]
+
+[[package]]
+name = "httpcore"
+version = "1.0.5"
+description = "A minimal low-level HTTP client."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "httpcore-1.0.5-py3-none-any.whl", hash = "sha256:421f18bac248b25d310f3cacd198d55b8e6125c107797b609ff9b7a6ba7991b5"},
+    {file = "httpcore-1.0.5.tar.gz", hash = "sha256:34a38e2f9291467ee3b44e89dd52615370e152954ba21721378a87b2960f7a61"},
+]
+
+[package.dependencies]
+certifi = "*"
+h11 = ">=0.13,<0.15"
+
+[package.extras]
+asyncio = ["anyio (>=4.0,<5.0)"]
+http2 = ["h2 (>=3,<5)"]
+socks = ["socksio (==1.*)"]
+trio = ["trio (>=0.22.0,<0.26.0)"]
+
+[[package]]
+name = "httpx"
+version = "0.27.0"
+description = "The next generation HTTP client."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "httpx-0.27.0-py3-none-any.whl", hash = "sha256:71d5465162c13681bff01ad59b2cc68dd838ea1f10e51574bac27103f00c91a5"},
+    {file = "httpx-0.27.0.tar.gz", hash = "sha256:a0cb88a46f32dc874e04ee956e4c2764aba2aa228f650b06788ba6bda2962ab5"},
+]
+
+[package.dependencies]
+anyio = "*"
+certifi = "*"
+httpcore = "==1.*"
+idna = "*"
+sniffio = "*"
+
+[package.extras]
+brotli = ["brotli", "brotlicffi"]
+cli = ["click (==8.*)", "pygments (==2.*)", "rich (>=10,<14)"]
+http2 = ["h2 (>=3,<5)"]
+socks = ["socksio (==1.*)"]
+
 [[package]]
 name = "huggingface-hub"
 version = "0.20.3"
@@ -1357,6 +1460,29 @@ files = [
 setuptools = "*"
 wheel = "*"
 
+[[package]]
+name = "openai"
+version = "1.16.2"
+description = "The official Python library for the openai API"
+optional = false
+python-versions = ">=3.7.1"
+files = [
+    {file = "openai-1.16.2-py3-none-any.whl", hash = "sha256:46a435380921e42dae218d04d6dd0e89a30d7f3b9d8a778d5887f78003cf9354"},
+    {file = "openai-1.16.2.tar.gz", hash = "sha256:c93d5efe5b73b6cb72c4cd31823852d2e7c84a138c0af3cbe4a8eb32b1164ab2"},
+]
+
+[package.dependencies]
+anyio = ">=3.5.0,<5"
+distro = ">=1.7.0,<2"
+httpx = ">=0.23.0,<1"
+pydantic = ">=1.9.0,<3"
+sniffio = "*"
+tqdm = ">4"
+typing-extensions = ">=4.7,<5"
+
+[package.extras]
+datalib = ["numpy (>=1)", "pandas (>=1.2.3)", "pandas-stubs (>=1.1.0.11)"]
+
 [[package]]
 name = "packaging"
 version = "23.2"
@@ -1799,6 +1925,23 @@ tomli = ">=1.0.0"
 [package.extras]
 testing = ["argcomplete", "hypothesis (>=3.56)", "mock", "nose", "pygments (>=2.7.2)", "requests", "xmlschema"]
 
+[[package]]
+name = "pytest-mock"
+version = "3.14.0"
+description = "Thin-wrapper around the mock package for easier use with pytest"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "pytest-mock-3.14.0.tar.gz", hash = "sha256:2719255a1efeceadbc056d6bf3df3d1c5015530fb40cf347c0f9afac88410bd0"},
+    {file = "pytest_mock-3.14.0-py3-none-any.whl", hash = "sha256:0b72c38033392a5f4621342fe11e9219ac11ec9d375f8e2a0c164539e0d70f6f"},
+]
+
+[package.dependencies]
+pytest = ">=6.2.5"
+
+[package.extras]
+dev = ["pre-commit", "pytest-asyncio", "tox"]
+
 [[package]]
 name = "python-dateutil"
 version = "2.8.2"
@@ -2360,6 +2503,17 @@ test = ["azure-common", "azure-core", "azure-storage-blob", "boto3", "google-clo
 webhdfs = ["requests"]
 zst = ["zstandard"]
 
+[[package]]
+name = "sniffio"
+version = "1.3.1"
+description = "Sniff out which async library your code is running under"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "sniffio-1.3.1-py3-none-any.whl", hash = "sha256:2f6da418d1f1e0fddd844478f41680e794e6051915791a034ff65e5f100525a2"},
+    {file = "sniffio-1.3.1.tar.gz", hash = "sha256:f4324edc670a0f49750a81b895f35c3adb843cca46f0530f79fc1babb23789dc"},
+]
+
 [[package]]
 name = "sudachidict-core"
 version = "20240109"
@@ -3185,4 +3339,4 @@ multidict = ">=4.0"
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.8.1,<4.0"
-content-hash = "6e7ddbb7e9d29824bd543489a80f8378e1be9b83131b5e6d0b0bf699a6a941f3"
+content-hash = "0a438df085b5f588ae2e896ccf7ae833860690af20528afac6bddc963abf564c"
diff --git a/pyproject.toml b/pyproject.toml
index 0f98250..49e05b4 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -27,6 +27,8 @@ torch = "2.0.0"  # this version is needed to avoid "libcu*" related errors
 pydantic = "^2.6.3"
 eval-type-backport = "^0.1.3"
 smart-open = "^7.0.1"
+openai = "^1.16.2"
+pytest-mock = "^3.14.0"
 
 [tool.poetry.group.dev.dependencies]
 black = "^23.11.0"
diff --git a/src/jmteb/embedders/__init__.py b/src/jmteb/embedders/__init__.py
index a1149d7..07399c5 100644
--- a/src/jmteb/embedders/__init__.py
+++ b/src/jmteb/embedders/__init__.py
@@ -1,2 +1,3 @@
 from jmteb.embedders.base import TextEmbedder
+from jmteb.embedders.openai_embedder import OpenAIEmbedder
 from jmteb.embedders.sbert_embedder import SentenceBertEmbedder
diff --git a/src/jmteb/embedders/openai_embedder.py b/src/jmteb/embedders/openai_embedder.py
new file mode 100644
index 0000000..63af35e
--- /dev/null
+++ b/src/jmteb/embedders/openai_embedder.py
@@ -0,0 +1,61 @@
+from __future__ import annotations
+
+import numpy as np
+from loguru import logger
+from openai import OpenAI
+
+from jmteb.embedders.base import TextEmbedder
+
+MODEL_DIM = {
+    "text-embedding-3-large": 3072,
+    "text-embedding-3-small": 1536,
+    "text-embedding-ada-002": 1536,
+}
+
+
+class OpenAIEmbedder(TextEmbedder):
+    """Embedder via OpenAI API."""
+
+    def __init__(self, model: str = "text-embedding-3-small", dim: int | None = None) -> None:
+        """Setup.
+        model and dim: see https://platform.openai.com/docs/models/embeddings
+        `text-embedding-3-large` model: max 3072 dim
+        `text-embedding-3-small` model: max 1536 dim
+        `text-embedding-ada-002` model: max 1536 dim
+
+        OpenAI embeddings have been normalized to length 1. See
+            https://platform.openai.com/docs/guides/embeddings/which-distance-function-should-i-use
+
+        Args:
+            model (str, optional): Name of an OpenAI embedding model. Defaults to "text-embedding-3-small".
+            dim (int, optional): Output dimension. Defaults to 1536.
+        """
+        self.client = OpenAI()  # API key written in .env
+        assert model in MODEL_DIM.keys(), f"`model` must be one of {list(MODEL_DIM.keys())}!"
+        self.model = model
+        if not dim:
+            self.dim = MODEL_DIM[self.model]
+        else:
+            if dim > MODEL_DIM[self.model]:
+                self.dim = MODEL_DIM[self.model]
+                logger.warning(f"The maximum dimension of model {self.model} is {self.dim}, use dim={self.dim}.")
+            else:
+                self.dim = dim
+
+    def encode(self, text: str | list[str]) -> np.ndarray:
+        result = np.asarray(
+            [
+                data.embedding
+                for data in self.client.embeddings.create(
+                    input=text,
+                    model=self.model,
+                    dimensions=self.dim,
+                ).data
+            ]
+        )
+        if result.shape[0] == 1:
+            return result.reshape(-1)
+        return result
+
+    def get_output_dim(self) -> int:
+        return self.dim
diff --git a/tests/embedders/test_openai.py b/tests/embedders/test_openai.py
new file mode 100644
index 0000000..e1c1302
--- /dev/null
+++ b/tests/embedders/test_openai.py
@@ -0,0 +1,69 @@
+from __future__ import annotations
+
+from dataclasses import dataclass
+
+import numpy as np
+import pytest
+from pytest_mock import MockerFixture
+
+from jmteb.embedders import OpenAIEmbedder, TextEmbedder
+
+OUTPUT_DIM = 1536  # the maximum dim of default model `text-embedding-3-small`
+
+
+@pytest.fixture(scope="function")
+def mock_openai_embedder(mocker: MockerFixture):
+    mocker.patch("jmteb.embedders.openai_embedder.OpenAI")
+    return OpenAIEmbedder(model="text-embedding-3-small")
+
+
+@dataclass
+class MockData:
+    data: list
+
+
+@dataclass
+class MockEmbedding:
+    embedding: list
+
+
+class MockOpenAIClientEmbedding:
+    def create(input: str | list[str], model: str, dimensions: int):
+        if isinstance(input, str):
+            input = [input]
+        return MockData(data=[MockEmbedding(embedding=[0.1] * dimensions)] * len(input))
+
+
+@pytest.mark.usefixtures("mock_openai_embedder")
+class TestOpenAIEmbedder:
+    @pytest.fixture(autouse=True)
+    def setup_class(cls, mocker: MockerFixture, mock_openai_embedder: TextEmbedder):
+        cls.model = mock_openai_embedder
+        cls.mock_create = mocker.patch.object(cls.model.client, "embeddings", new=MockOpenAIClientEmbedding)
+
+    def test_encode(self):
+        embeddings = self.model.encode("任意のテキスト")
+        assert isinstance(embeddings, np.ndarray)
+        assert embeddings.shape == (OUTPUT_DIM,)
+
+    def test_encode_multiple(self):
+        embeddings = self.model.encode(["任意のテキスト"] * 3)
+        assert isinstance(embeddings, np.ndarray)
+        assert embeddings.shape == (3, OUTPUT_DIM)
+
+    def test_get_output_dim(self):
+        assert self.model.get_output_dim() == OUTPUT_DIM
+
+    def test_nonexistent_model(self):
+        with pytest.raises(AssertionError):
+            _ = OpenAIEmbedder(model="model")
+
+    def test_model_dim(self):
+        assert OpenAIEmbedder(model="text-embedding-3-large").dim == 3072
+        assert OpenAIEmbedder(model="text-embedding-ada-002").dim == 1536
+
+    def test_dim_over_max(self):
+        assert OpenAIEmbedder(dim=2 * OUTPUT_DIM).dim == OUTPUT_DIM
+
+    def test_dim_smaller(self):
+        assert OpenAIEmbedder(dim=OUTPUT_DIM // 2).dim == OUTPUT_DIM // 2