diff --git a/.github/workflows/aryn-sdk_release.yml b/.github/workflows/aryn-sdk_release.yml
index 1e41e0bf8..6046d2028 100644
--- a/.github/workflows/aryn-sdk_release.yml
+++ b/.github/workflows/aryn-sdk_release.yml
@@ -11,7 +11,7 @@ permissions:
 jobs:
   release:
     name: Upload to PyPI
-    runs-on: blacksmith-4vcpu-ubuntu-2204
+    runs-on: ubuntu-latest
     environment:
       name: PyPI
       url: https://pypi.org/project/aryn-sdk/
@@ -22,7 +22,7 @@ jobs:
         uses: actions/checkout@v4
       - name: Install poetry
         run: pipx install poetry
-      - uses: useblacksmith/setup-python@v6
+      - uses: actions/setup-python@v4
         with:
           python-version: "3.11"
           cache: "poetry"
diff --git a/.github/workflows/codeql.yml b/.github/workflows/codeql.yml
index cc924cc57..29d87a585 100644
--- a/.github/workflows/codeql.yml
+++ b/.github/workflows/codeql.yml
@@ -21,7 +21,7 @@ on:
 
 jobs:
   analyze:
-    runs-on: 'blacksmith'
+    runs-on: 'ubuntu-latest'
     permissions:
       # required for all workflows
       security-events: write
diff --git a/.github/workflows/dependency-review.yml b/.github/workflows/dependency-review.yml
index bcc14e5a6..59b08c6a1 100644
--- a/.github/workflows/dependency-review.yml
+++ b/.github/workflows/dependency-review.yml
@@ -18,7 +18,7 @@ permissions:
 
 jobs:
   dependency-review:
-    runs-on: blacksmith
+    runs-on: ubuntu-latest
     steps:
       - name: 'Checkout repository'
         uses: actions/checkout@v4
diff --git a/.github/workflows/doclint.yml b/.github/workflows/doclint.yml
index 4c97b2c4f..075d7ba9e 100644
--- a/.github/workflows/doclint.yml
+++ b/.github/workflows/doclint.yml
@@ -9,7 +9,7 @@ on:
 
 jobs:
   doclint:
-    runs-on: blacksmith-4vcpu-ubuntu-2204
+    runs-on: ubuntu-latest
     steps:
       - name: Checkout
         uses: actions/checkout@v4
diff --git a/.github/workflows/draft_release.yml b/.github/workflows/draft_release.yml
index b081c32af..916f4e220 100644
--- a/.github/workflows/draft_release.yml
+++ b/.github/workflows/draft_release.yml
@@ -10,13 +10,13 @@ permissions:
 
 jobs:
   draft-release:
-    runs-on: blacksmith-4vcpu-ubuntu-2204
+    runs-on: ubuntu-latest
     steps:
       - name: Checkout
         uses: actions/checkout@v4
       - name: Install poetry
         run: pipx install poetry
-      - uses: useblacksmith/setup-python@v6
+      - uses: actions/setup-python@v4
         with:
           python-version: '3.11'
           cache: 'poetry'
diff --git a/.github/workflows/linting.yml b/.github/workflows/linting.yml
index 9bfb409e4..0cb1c7169 100644
--- a/.github/workflows/linting.yml
+++ b/.github/workflows/linting.yml
@@ -11,7 +11,7 @@ on:
 # specific.
 jobs:
   mypy:
-    runs-on: blacksmith-4vcpu-ubuntu-2204
+    runs-on: ubuntu-latest
     steps:
       - name: DF-1
         run: df -h
@@ -29,7 +29,7 @@ jobs:
         run: df -h
       - name: Install poetry
         run: pipx install poetry
-      - uses: useblacksmith/setup-python@v6
+      - uses: actions/setup-python@v4
         with:
           python-version: '3.9'
           cache: 'poetry'
@@ -45,13 +45,13 @@ jobs:
           poetry run mypy --install-types --non-interactive .
 
   lint:
-    runs-on: blacksmith-4vcpu-ubuntu-2204
+    runs-on: ubuntu-latest
     steps:
       - name: Checkout
         uses: actions/checkout@v4
       - name: Install poetry
         run: pipx install poetry
-      - uses: useblacksmith/setup-python@v6
+      - uses: actions/setup-python@v4
         with:
           python-version: '3.9'
           cache: 'poetry'
diff --git a/.github/workflows/pypi_release.yml b/.github/workflows/pypi_release.yml
index a58a18246..5d0c0f1d4 100644
--- a/.github/workflows/pypi_release.yml
+++ b/.github/workflows/pypi_release.yml
@@ -5,7 +5,7 @@ on:
 jobs:
   test-pypi-release:
     name: Upload to PyPI
-    runs-on: blacksmith-4vcpu-ubuntu-2204
+    runs-on: ubuntu-latest
     environment:
       name: PyPI
       url: https://pypi.org/project/sycamore-ai/
@@ -16,7 +16,7 @@ jobs:
         uses: actions/checkout@v4
       - name: Install poetry
         run: pipx install poetry
-      - uses: useblacksmith/setup-python@v6
+      - uses: actions/setup-python@v4
         with:
           python-version: "3.11"
           cache: "poetry"
diff --git a/.github/workflows/testing.yml b/.github/workflows/testing.yml
index 584f2ad96..d2ba78bff 100644
--- a/.github/workflows/testing.yml
+++ b/.github/workflows/testing.yml
@@ -12,6 +12,7 @@ on:
 env:
   OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
   ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
+  GEMINI_API_KEY: ${{ secrets.GEMINI_API_KEY }}
   AZURE_OPENAI_API_KEY: ${{ secrets.AZURE_OPENAI_API_KEY }}
   SYCAMORE_S3_TEMP_PATH: s3://aryn-sycamore-integ-temp/
   MODEL_SERVER_KEY: ${{ secrets.MODEL_SERVER_KEY }}
@@ -30,7 +31,7 @@ permissions:
 
 jobs:
   sycamore-unit-tests:
-    runs-on: blacksmith-8vcpu-ubuntu-2204
+    runs-on: ubuntu-latest
     strategy:
       matrix:
         python-version: ["3.9", "3.10", "3.11", "3.12"]
@@ -53,7 +54,7 @@ jobs:
       - name: Install poetry
         run: pipx install poetry
       - name: Set up Python ${{ matrix.python-version }}
-        uses: useblacksmith/setup-python@v6
+        uses: actions/setup-python@v4
         with:
           python-version: ${{ matrix.python-version }}
           cache: "poetry"
diff --git a/lib/sycamore/poetry.lock b/lib/sycamore/poetry.lock
index 5dae06d42..80fee5f95 100644
--- a/lib/sycamore/poetry.lock
+++ b/lib/sycamore/poetry.lock
@@ -2459,6 +2459,22 @@ pyopenssl = ["cryptography (>=38.0.3)", "pyopenssl (>=20.0.0)"]
 reauth = ["pyu2f (>=0.1.5)"]
 requests = ["requests (>=2.20.0,<3.0.0.dev0)"]
 
+[[package]]
+name = "google-genai"
+version = "1.1.0"
+description = "GenAI Python SDK"
+optional = true
+python-versions = ">=3.9"
+files = [
+    {file = "google_genai-1.1.0-py3-none-any.whl", hash = "sha256:c48ac44612ad6aadc0bf96b12fa4314756baa16382c890fff793bcb53e9a9cc8"},
+]
+
+[package.dependencies]
+google-auth = ">=2.14.1,<3.0.0dev"
+pydantic = ">=2.0.0,<3.0.0dev"
+requests = ">=2.28.1,<3.0.0dev"
+websockets = ">=13.0,<15.0dev"
+
 [[package]]
 name = "googleapis-common-protos"
 version = "1.66.0"
@@ -9422,6 +9438,84 @@ docs = ["Sphinx (>=6.0)", "myst-parser (>=2.0.0)", "sphinx-rtd-theme (>=1.1.0)"]
 optional = ["python-socks", "wsaccel"]
 test = ["websockets"]
 
+[[package]]
+name = "websockets"
+version = "14.2"
+description = "An implementation of the WebSocket Protocol (RFC 6455 & 7692)"
+optional = true
+python-versions = ">=3.9"
+files = [
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+    {file = "websockets-14.2-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:dec254fcabc7bd488dab64846f588fc5b6fe0d78f641180030f8ea27b76d72c3"},
+    {file = "websockets-14.2-pp39-pypy39_pp73-macosx_10_15_x86_64.whl", hash = "sha256:bbe03eb853e17fd5b15448328b4ec7fb2407d45fb0245036d06a3af251f8e48f"},
+    {file = "websockets-14.2-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:a3c4aa3428b904d5404a0ed85f3644d37e2cb25996b7f096d77caeb0e96a3b42"},
+    {file = "websockets-14.2-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:577a4cebf1ceaf0b65ffc42c54856214165fb8ceeba3935852fc33f6b0c55e7f"},
+    {file = "websockets-14.2-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ad1c1d02357b7665e700eca43a31d52814ad9ad9b89b58118bdabc365454b574"},
+    {file = "websockets-14.2-pp39-pypy39_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f390024a47d904613577df83ba700bd189eedc09c57af0a904e5c39624621270"},
+    {file = "websockets-14.2-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:3c1426c021c38cf92b453cdf371228d3430acd775edee6bac5a4d577efc72365"},
+    {file = "websockets-14.2-py3-none-any.whl", hash = "sha256:7a6ceec4ea84469f15cf15807a747e9efe57e369c384fa86e022b3bea679b79b"},
+    {file = "websockets-14.2.tar.gz", hash = "sha256:5059ed9c54945efb321f097084b4c7e52c246f2c869815876a69d1efc4ad6eb5"},
+]
+
 [[package]]
 name = "wget"
 version = "3.2"
@@ -9849,6 +9943,7 @@ docs = ["furo", "myst-parser", "sphinx"]
 duckdb = ["duckdb"]
 elasticsearch = ["elasticsearch"]
 eval = ["apted", "datasets", "rouge"]
+google-genai = ["google-genai"]
 legacy-partitioners = ["nltk", "python-pptx", "unstructured"]
 local-inference = ["easyocr", "paddleocr", "pdfminer-six", "pytesseract", "sentence-transformers", "timm", "torch", "torchvision", "transformers"]
 neo4j = ["neo4j"]
@@ -9860,4 +9955,4 @@ weaviate = ["weaviate-client"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9,<3.13"
-content-hash = "fda09c7256e9192143850b2748859c429b88eb8d2db0a957d489a7abe954409d"
+content-hash = "d8ce4686a3c23cb77033c0c0d64402451de6ef501d04083fcd3deeafc1fc0897"
diff --git a/lib/sycamore/pyproject.toml b/lib/sycamore/pyproject.toml
index 8594f247d..1e37404bd 100644
--- a/lib/sycamore/pyproject.toml
+++ b/lib/sycamore/pyproject.toml
@@ -88,6 +88,7 @@ nltk = { version = "^3.9.0", optional = true }
 
 # LLM Dependencies
 anthropic = { version = "^0.42.0", optional = true }
+google-genai = {version = "^1.0", optional = true}
 tiktoken = "^0.8.0"
 
 [tool.poetry.group.test.dependencies]
@@ -143,6 +144,7 @@ legacy-partitioners = ["unstructured", "python-pptx", "nltk"]
 
 # LLM extras
 anthropic = ["anthropic"]
+google-genai = ["google-genai"]
 
 [tool.ruff]
 line-length = 120
diff --git a/lib/sycamore/sycamore/llms/__init__.py b/lib/sycamore/sycamore/llms/__init__.py
index 8515fe4bb..a05c3f752 100644
--- a/lib/sycamore/sycamore/llms/__init__.py
+++ b/lib/sycamore/sycamore/llms/__init__.py
@@ -4,6 +4,7 @@
 from sycamore.llms.openai import OpenAI, OpenAIClientType, OpenAIModels, OpenAIClientParameters, OpenAIClientWrapper
 from sycamore.llms.bedrock import Bedrock, BedrockModels
 from sycamore.llms.anthropic import Anthropic, AnthropicModels
+from sycamore.llms.gemini import Gemini, GeminiModels
 
 # Register the model constructors.
 MODELS: Dict[str, Callable[..., LLM]] = {}
@@ -16,6 +17,7 @@
 MODELS.update(
     {f"anthropic.{model.value}": lambda **kwargs: Anthropic(model.value, **kwargs) for model in AnthropicModels}
 )
+MODELS.update({f"gemini.{model.value}": lambda **kwargs: Gemini(model.value.name, **kwargs) for model in GeminiModels})
 
 
 def get_llm(model_name: str) -> Callable[..., LLM]:
@@ -38,4 +40,6 @@ def get_llm(model_name: str) -> Callable[..., LLM]:
     "BedrockModels",
     "Anthropic",
     "AnthropicModels",
+    "Gemini",
+    "GeminiModels",
 ]
diff --git a/lib/sycamore/sycamore/llms/gemini.py b/lib/sycamore/sycamore/llms/gemini.py
new file mode 100644
index 000000000..b4dc14607
--- /dev/null
+++ b/lib/sycamore/sycamore/llms/gemini.py
@@ -0,0 +1,136 @@
+from dataclasses import dataclass
+import datetime
+from enum import Enum
+from typing import Any, Optional, Union
+import os
+
+from sycamore.llms.llms import LLM
+from sycamore.llms.prompts.prompts import RenderedPrompt
+from sycamore.utils.cache import Cache
+from sycamore.utils.import_utils import requires_modules
+
+DEFAULT_MAX_TOKENS = 1024
+
+
+@dataclass
+class GeminiModel:
+    name: str
+    is_chat: bool = False
+
+
+class GeminiModels(Enum):
+    """Represents available Gemini models. More info: https://googleapis.github.io/python-genai/"""
+
+    # Note that the models available on a given Gemini account may vary.
+    GEMINI_2_FLASH = GeminiModel(name="gemini-2.0-flash-exp", is_chat=True)
+    GEMINI_2_FLASH_LITE = GeminiModel(name="gemini-2.0-flash-lite-preview-02-05", is_chat=True)
+    GEMINI_2_FLASH_THINKING = GeminiModel(name="gemini-2.0-flash-thinking-exp", is_chat=True)
+    GEMINI_2_PRO = GeminiModel(name="gemini-2.0-pro-exp", is_chat=True)
+
+    @classmethod
+    def from_name(cls, name: str):
+        for m in iter(cls):
+            if m.value.name == name:
+                return m
+        return None
+
+
+class Gemini(LLM):
+    """This is an LLM implementation that uses the Google Gemini API to generate text.
+
+    Args:
+        model_name: The name of the Gemini model to use.
+        cache: A cache object to use for caching results.
+    """
+
+    @requires_modules("google.genai", extra="google-genai")
+    def __init__(
+        self,
+        model_name: Union[GeminiModels, str],
+        cache: Optional[Cache] = None,
+        api_key: Optional[str] = None,
+    ):
+        from google.genai import Client
+
+        self.model_name = model_name
+
+        if isinstance(model_name, GeminiModels):
+            self.model = model_name.value
+        elif isinstance(model_name, str):
+            self.model = GeminiModel(name=model_name)
+        api_key = api_key if api_key else os.getenv("GEMINI_API_KEY")
+        self._client = Client(api_key=api_key)
+        super().__init__(self.model.name, cache)
+
+    def __reduce__(self):
+        def deserializer(kwargs):
+            return Gemini(**kwargs)
+
+        kwargs = {"model_name": self.model_name, "cache": self._cache}
+        return deserializer, (kwargs,)
+
+    def is_chat_mode(self) -> bool:
+        """Returns True if the LLM is in chat mode, False otherwise."""
+        return True
+
+    def get_generate_kwargs(self, prompt: RenderedPrompt, llm_kwargs: Optional[dict] = None) -> dict:
+        from google.genai import types
+
+        kwargs: dict[str, Any] = {}
+        config = {
+            "temperature": 0,
+            "candidate_count": 1,
+            **(llm_kwargs or {}),
+        }
+        config["max_output_tokens"] = config.get("max_output_tokens", DEFAULT_MAX_TOKENS)
+        if prompt.response_format:
+            config["response_mime_type"] = "application/json"
+            config["response_schema"] = prompt.response_format
+        content_list = []
+        for message in prompt.messages:
+            if message.role == "system":
+                config["system_message"] = message.content
+                continue
+            role = "model" if message.role == "assistant" else "user"
+            content = types.Content(parts=[types.Part.from_text(text=message.content)], role=role)
+            if message.images:
+                for image in message.images:
+                    image_bytes = image.convert("RGB").tobytes()
+                    content.parts.append(types.Part.from_bytes(image_bytes, media_type="image/png"))
+            content_list.append(content)
+        kwargs["config"] = None
+        if config:
+            kwargs["config"] = types.GenerateContentConfig(**config)
+        kwargs["content"] = content
+        return kwargs
+
+    def generate_metadata(self, *, prompt: RenderedPrompt, llm_kwargs: Optional[dict] = None) -> dict:
+        ret = self._llm_cache_get(prompt, llm_kwargs)
+        if isinstance(ret, dict):
+            return ret
+        assert ret is None
+
+        kwargs = self.get_generate_kwargs(prompt, llm_kwargs)
+
+        start = datetime.datetime.now()
+        response = self._client.models.generate_content(
+            model=self.model.name, contents=kwargs["content"], config=kwargs["config"]
+        )
+        wall_latency = datetime.datetime.now() - start
+        md = response.usage_metadata
+        in_tokens = int(md.prompt_token_count) if md and md.prompt_token_count else 0
+        out_tokens = int(md.candidates_token_count) if md and md.candidates_token_count else 0
+        output = " ".join(part.text if part else "" for part in response.candidates[0].content.parts)
+        ret = {
+            "output": output,
+            "wall_latency": wall_latency,
+            "in_tokens": in_tokens,
+            "out_tokens": out_tokens,
+        }
+        self.add_llm_metadata(kwargs, output, wall_latency, in_tokens, out_tokens)
+        self._llm_cache_set(prompt, llm_kwargs, ret)
+        return ret
+
+    def generate(self, *, prompt: RenderedPrompt, llm_kwargs: Optional[dict] = None) -> str:
+        d = self.generate_metadata(prompt=prompt, llm_kwargs=llm_kwargs)
+        return d["output"]
diff --git a/lib/sycamore/sycamore/tests/integration/llms/test_gemini.py b/lib/sycamore/sycamore/tests/integration/llms/test_gemini.py
new file mode 100644
index 000000000..1994ca447
--- /dev/null
+++ b/lib/sycamore/sycamore/tests/integration/llms/test_gemini.py
@@ -0,0 +1,153 @@
+from pathlib import Path
+from typing import Any
+import base64
+import pickle
+
+from sycamore.llms import Gemini, GeminiModels
+from sycamore.llms.prompts.prompts import RenderedPrompt, RenderedMessage
+from sycamore.utils.cache import DiskCache
+
+
+def cacheget(cache: DiskCache, key: str):
+    hit = cache.get(key)
+    return pickle.loads(base64.b64decode(hit))  # type: ignore
+
+
+def cacheset(cache: DiskCache, key: str, data: Any):
+    databytes = pickle.dumps(data)
+    cache.set(key, base64.b64encode(databytes).decode("utf-8"))
+
+
+def test_gemini_defaults():
+    llm = Gemini(GeminiModels.GEMINI_2_FLASH)
+    prompt = RenderedPrompt(
+        messages=[RenderedMessage(role="user", content="Write a limerick about large language models.")]
+    )
+
+    res = llm.generate(prompt=prompt, llm_kwargs={})
+
+    assert len(res) > 0
+
+
+def test_gemini_messages_defaults():
+    llm = Gemini(GeminiModels.GEMINI_2_FLASH)
+    messages = [
+        RenderedMessage(
+            role="user",
+            content="Write a caption for a recent trip to a sunny beach",
+        ),
+    ]
+    prompt = RenderedPrompt(messages=messages)
+
+    res = llm.generate(prompt=prompt, llm_kwargs={})
+
+    assert len(res) > 0
+
+
+def test_cached_gemini(tmp_path: Path):
+    cache = DiskCache(str(tmp_path))
+    llm = Gemini(GeminiModels.GEMINI_2_FLASH, cache=cache)
+    prompt = RenderedPrompt(
+        messages=[RenderedMessage(role="user", content="Write a limerick about large language models.")]
+    )
+
+    # pylint: disable=protected-access
+    key = llm._llm_cache_key(prompt, {})
+
+    res = llm.generate(prompt=prompt, llm_kwargs={})
+
+    # assert result is cached
+    assert cacheget(cache, key).get("result")["output"] == res
+    assert cacheget(cache, key).get("prompt") == prompt
+    assert cacheget(cache, key).get("prompt.response_format") is None
+    assert cacheget(cache, key).get("llm_kwargs") == {}
+    assert cacheget(cache, key).get("model_name") == GeminiModels.GEMINI_2_FLASH.value.name
+
+    # assert llm.generate is using cached result
+    custom_output: dict[str, Any] = {
+        "result": {"output": "This is a custom response"},
+        "prompt": prompt,
+        "prompt.response_format": None,
+        "llm_kwargs": {},
+        "model_name": GeminiModels.GEMINI_2_FLASH.value.name,
+    }
+    cacheset(cache, key, custom_output)
+
+    assert llm.generate(prompt=prompt, llm_kwargs={}) == custom_output["result"]["output"]
+
+
+def test_cached_gemini_different_prompts(tmp_path: Path):
+    cache = DiskCache(str(tmp_path))
+    llm = Gemini(GeminiModels.GEMINI_2_FLASH, cache=cache)
+    prompt_1 = RenderedPrompt(
+        messages=[RenderedMessage(role="user", content="Write a limerick about large language models.")]
+    )
+    prompt_2 = RenderedPrompt(
+        messages=[RenderedMessage(role="user", content="Write a short limerick about large language models.")]
+    )
+    prompt_3 = RenderedPrompt(
+        messages=[RenderedMessage(role="user", content="Write a poem about large language models.")]
+    )
+    prompt_4 = RenderedPrompt(
+        messages=[RenderedMessage(role="user", content="Write a short poem about large language models.")]
+    )
+
+    key_1 = llm._llm_cache_key(prompt_1, {})
+    key_2 = llm._llm_cache_key(prompt_2, {})
+    key_3 = llm._llm_cache_key(prompt_3, {})
+    key_4 = llm._llm_cache_key(prompt_4, {})
+    keys = [key_1, key_2, key_3, key_4]
+
+    assert len(keys) == len(
+        set(keys)
+    ), f"""
+    Cached query keys are not unique:
+    key_1: {key_1}
+    key_2: {key_2}
+    key_3: {key_3}
+    key_4: {key_4}
+    """
+
+
+def test_cached_gemini_different_models(tmp_path: Path):
+    cache = DiskCache(str(tmp_path))
+    llm_FLASH = Gemini(GeminiModels.GEMINI_2_FLASH, cache=cache)
+    llm_FLASH_LITE = Gemini(GeminiModels.GEMINI_2_FLASH_LITE, cache=cache)
+
+    prompt = RenderedPrompt(
+        messages=[RenderedMessage(role="user", content="Write a limerick about large language models.")]
+    )
+
+    # populate cache
+    key_FLASH = llm_FLASH._llm_cache_key(prompt, {})
+    res_FLASH = llm_FLASH.generate(prompt=prompt, llm_kwargs={})
+    key_FLASH_LITE = llm_FLASH_LITE._llm_cache_key(prompt, {})
+    res_FLASH_LITE = llm_FLASH_LITE.generate(prompt=prompt, llm_kwargs={})
+
+    # check proper cached results
+    assert cacheget(cache, key_FLASH_LITE).get("result")["output"] == res_FLASH_LITE
+    assert cacheget(cache, key_FLASH_LITE).get("prompt") == prompt
+    assert cacheget(cache, key_FLASH_LITE).get("llm_kwargs") == {}
+    assert cacheget(cache, key_FLASH_LITE).get("model_name") == GeminiModels.GEMINI_2_FLASH_LITE.value.name
+    assert cacheget(cache, key_FLASH).get("result")["output"] == res_FLASH
+    assert cacheget(cache, key_FLASH).get("prompt") == prompt
+    assert cacheget(cache, key_FLASH).get("llm_kwargs") == {}
+    assert cacheget(cache, key_FLASH).get("model_name") == GeminiModels.GEMINI_2_FLASH.value.name
+
+    # check for difference with model change
+    assert key_FLASH != key_FLASH_LITE
+    assert res_FLASH != res_FLASH_LITE
+
+
+def test_metadata():
+    llm = Gemini(GeminiModels.GEMINI_2_FLASH)
+    prompt = RenderedPrompt(
+        messages=[RenderedMessage(role="user", content="Write a limerick about large language models.")]
+    )
+
+    res = llm.generate_metadata(prompt=prompt, llm_kwargs={})
+
+    assert "output" in res
+    assert "wall_latency" in res
+    assert "in_tokens" in res
+    assert "out_tokens" in res
diff --git a/lib/sycamore/sycamore/transforms/summarize_images.py b/lib/sycamore/sycamore/transforms/summarize_images.py
index 7be07fb40..dfe237211 100644
--- a/lib/sycamore/sycamore/transforms/summarize_images.py
+++ b/lib/sycamore/sycamore/transforms/summarize_images.py
@@ -1,10 +1,11 @@
 from typing import Optional
 
+from PIL import Image
 
 from sycamore.data import Document, Element
-from sycamore.llms.openai import LLM, OpenAI, OpenAIClientWrapper, OpenAIModels
+from sycamore.llms import LLM, OpenAI, OpenAIClientWrapper, OpenAIModels, Gemini, GeminiModels
 from sycamore.llms.prompts.default_prompts import SummarizeImagesJinjaPrompt
-from sycamore.llms.prompts.prompts import SycamorePrompt
+from sycamore.llms.prompts.prompts import SycamorePrompt, RenderedMessage, RenderedPrompt
 from sycamore.plan_nodes import Node
 from sycamore.transforms.base import CompositeTransform
 from sycamore.transforms.base_llm import LLMMapElements
@@ -81,6 +82,23 @@ def __init__(self, llm: LLM, prompt: Optional[str] = None, include_context: bool
         self.prompt = prompt
         self.include_context = include_context
 
+    def summarize_image(self, image: Image.Image, context: Optional[str]) -> str:
+        """Summarize the image using the LLM. Helper method to use this class without creating an instance.
+
+        Args:
+            image: The image to summarize.
+            context: The context to use for summarization.
+
+        Returns:
+            The summarized image as a string.
+        """
+        messages = []
+        if context is not None:
+            messages = [RenderedMessage(role="system", content=context)]
+        messages.append(RenderedMessage(role="user", content=self.prompt, images=[image]))
+
+        return self.llm.generate(prompt=RenderedPrompt(messages=messages))
+
 
 class OpenAIImageSummarizer(LLMImageSummarizer):
     """Implementation of the LLMImageSummarizer for OpenAI models.
@@ -110,6 +128,28 @@ def __init__(
         super().__init__(llm=openai, prompt=prompt, include_context=include_context)
 
 
+class GeminiImageSummarizer(LLMImageSummarizer):
+    """Implementation of the LLMImageSummarizer for Gemini models.
+
+    Args:
+       gemini_model: The Gemini instance to use. If not set, one will be created.
+       prompt: The prompt to use to pass to the model, as a string.
+       include_context: Whether to include the immediately preceding and following text elements as context.
+    """
+
+    model = GeminiModels.GEMINI_2_FLASH
+
+    def __init__(
+        self,
+        gemini_model: Optional[Gemini] = None,
+        prompt: Optional[str] = None,
+        include_context: bool = True,
+    ):
+        if gemini_model is None:
+            gemini_model = Gemini(model_name=self.model)
+        super().__init__(llm=gemini_model, prompt=prompt, include_context=include_context)
+
+
 class SummarizeImages(CompositeTransform):
     """SummarizeImages is a transform for summarizing context into text using an LLM.
 
diff --git a/poetry.lock b/poetry.lock
index 26fb92ed7..5fc4c37ab 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -2735,6 +2735,23 @@ files = [
 [package.extras]
 testing = ["pytest"]
 
+[[package]]
+name = "google-genai"
+version = "1.2.0"
+description = "GenAI Python SDK"
+optional = false
+python-versions = ">=3.9"
+files = [
+    {file = "google_genai-1.2.0-py3-none-any.whl", hash = "sha256:609d61bee73f1a6ae5b47e9c7dd4b469d50318f050c5ceacf835b0f80f79d2d9"},
+]
+
+[package.dependencies]
+google-auth = ">=2.14.1,<3.0.0dev"
+pydantic = ">=2.0.0,<3.0.0dev"
+requests = ">=2.28.1,<3.0.0dev"
+typing-extensions = ">=4.11.0,<5.0.0dev"
+websockets = ">=13.0,<15.0dev"
+
 [[package]]
 name = "google-resumable-media"
 version = "2.7.2"
@@ -8668,6 +8685,7 @@ elasticsearch = {version = "8.14.0", optional = true}
 fasteners = "^0.19"
 fsspec = "2024.2.0"
 furo = {version = "^2023.9.10", optional = true}
+google-genai = {version = "^1.0", optional = true}
 jinja2 = "^3.1.5"
 myst-parser = {version = "^2.0.0", optional = true}
 nanoid = "^2.0.0"
@@ -8714,6 +8732,7 @@ docs = ["furo (>=2023.9.10,<2024.0.0)", "myst-parser (>=2.0.0,<3.0.0)", "sphinx
 duckdb = ["duckdb (>=1.1.1,<2.0.0)"]
 elasticsearch = ["elasticsearch (==8.14.0)"]
 eval = ["apted (>=1.0.3,<2.0.0)", "datasets (>=2.16.1,<3.0.0)", "rouge (>=1.0.1,<2.0.0)"]
+google-genai = ["google-genai (>=1.0,<2.0)"]
 legacy-partitioners = ["nltk (>=3.9.0,<4.0.0)", "python-pptx (>=0.6.22,<0.7.0)", "unstructured (==0.10.20)"]
 local-inference = ["easyocr (>=1.7.1,<2.0.0)", "paddleocr (>=2.8.1,<3.0.0)", "pdfminer-six (==20221105)", "pytesseract (>=0.3.10,<0.4.0)", "sentence-transformers (>=3.0.1,<4.0.0)", "timm (>=0.9.12,<0.10.0)", "torch (>=2.3.0,<3.0.0)", "torchvision (>=0.18.1,<0.19.0)", "transformers (>=4.43.1,<5.0.0)"]
 neo4j = ["neo4j (>=5.21.0,<6.0.0)"]
@@ -9747,6 +9766,84 @@ docs = ["Sphinx (>=6.0)", "myst-parser (>=2.0.0)", "sphinx-rtd-theme (>=1.1.0)"]
 optional = ["python-socks", "wsaccel"]
 test = ["websockets"]
 
+[[package]]
+name = "websockets"
+version = "14.2"
+description = "An implementation of the WebSocket Protocol (RFC 6455 & 7692)"
+optional = false
+python-versions = ">=3.9"
+files = [
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+]
+
 [[package]]
 name = "wget"
 version = "3.2"
@@ -10174,4 +10271,4 @@ docs = ["furo", "myst-parser", "sphinx"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9,<3.9.7 || >3.9.7,<3.13"
-content-hash = "3d009dae5d60345a770686b4bb252378c4be106e06b0050f07200e8d3d63daef"
+content-hash = "0768fecd2fa721235599a3bb1c07d636b71f7da568ccee6b09e816a54337a4e3"
diff --git a/pyproject.toml b/pyproject.toml
index 1434984cb..fad9d629c 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -34,7 +34,7 @@ pytest = "^7.4"
 pytest-mock = "^3.11"
 
 [tool.poetry.group.dev.dependencies]
-sycamore-ai = { path = "lib/sycamore", develop = true, extras=["eval", "duckdb", "elasticsearch", "neo4j", "opensearch", "pinecone", "weaviate", "local-inference", "legacy-partitioners", "anthropic"] }
+sycamore-ai = { path = "lib/sycamore", develop = true, extras=["eval", "duckdb", "elasticsearch", "neo4j", "opensearch", "pinecone", "weaviate", "local-inference", "legacy-partitioners", "anthropic", "google-genai"] }
 remote-processors = { path = "lib/remote-processors", develop = true }
 integration = { path = "apps/integration", develop = true }
 sycamore-poetry-lock = { path = "lib/poetry-lock", develop = true }