diff --git a/docker/Dockerfile.pip b/docker/Dockerfile.pip
index 2bac17db..dcdca3ee 100644
--- a/docker/Dockerfile.pip
+++ b/docker/Dockerfile.pip
@@ -18,7 +18,7 @@ ARG CUDA_VERSION=11.8.0
 FROM nvidia/cuda:${CUDA_VERSION}-devel-ubuntu22.04
 
 ARG PYSPARK_VERSION=3.3.1
-ARG RAPIDS_VERSION=23.10.0
+ARG RAPIDS_VERSION=23.12.0
 ARG ARCH=amd64
 #ARG ARCH=arm64
 # Install packages to build spark-rapids-ml
diff --git a/docker/Dockerfile.python b/docker/Dockerfile.python
index bd45fc74..2e3fd3bf 100644
--- a/docker/Dockerfile.python
+++ b/docker/Dockerfile.python
@@ -17,7 +17,7 @@
 ARG CUDA_VERSION=11.8.0
 FROM nvidia/cuda:${CUDA_VERSION}-devel-ubuntu20.04
 
-ARG CUML_VERSION=23.10
+ARG CUML_VERSION=23.12
 
 # Install packages to build spark-rapids-ml
 RUN apt update -y \
diff --git a/jvm/README.md b/jvm/README.md
index c72cf88f..af9ab16d 100644
--- a/jvm/README.md
+++ b/jvm/README.md
@@ -94,8 +94,8 @@ repository, usually in your `~/.m2/repository`.
 
 Add the artifact jar to the Spark, for example:
 ```bash
-ML_JAR="target/rapids-4-spark-ml_2.12-23.10.0-SNAPSHOT.jar"
-PLUGIN_JAR="~/.m2/repository/com/nvidia/rapids-4-spark_2.12/23.10.0/rapids-4-spark_2.12-23.10.0.jar"
+ML_JAR="target/rapids-4-spark-ml_2.12-23.12.0-SNAPSHOT.jar"
+PLUGIN_JAR="~/.m2/repository/com/nvidia/rapids-4-spark_2.12/23.12.0/rapids-4-spark_2.12-23.12.1.jar"
 
 $SPARK_HOME/bin/spark-shell --master $SPARK_MASTER \
  --driver-memory 20G \
diff --git a/notebooks/aws-emr/init-bootstrap-action.sh b/notebooks/aws-emr/init-bootstrap-action.sh
index d2096831..f1bd4276 100755
--- a/notebooks/aws-emr/init-bootstrap-action.sh
+++ b/notebooks/aws-emr/init-bootstrap-action.sh
@@ -8,7 +8,7 @@ sudo chmod a+rwx -R /sys/fs/cgroup/devices
 sudo yum install -y gcc openssl-devel bzip2-devel libffi-devel tar gzip wget make mysql-devel
 sudo bash -c "wget https://www.python.org/ftp/python/3.9.9/Python-3.9.9.tgz && tar xzf Python-3.9.9.tgz && cd Python-3.9.9 && ./configure --enable-optimizations && make altinstall"
 
-RAPIDS_VERSION=23.10.0
+RAPIDS_VERSION=23.12.0
 
 # install scikit-learn 
 sudo /usr/local/bin/pip3.9 install scikit-learn
diff --git a/notebooks/databricks/README.md b/notebooks/databricks/README.md
index 97f475ce..9c425dbe 100644
--- a/notebooks/databricks/README.md
+++ b/notebooks/databricks/README.md
@@ -44,7 +44,7 @@ If you already have a Databricks account, you can run the example notebooks on a
       spark.task.resource.gpu.amount 1
       spark.databricks.delta.preview.enabled true
       spark.python.worker.reuse true
-      spark.executorEnv.PYTHONPATH /databricks/jars/rapids-4-spark_2.12-23.10.0.jar:/databricks/spark/python
+      spark.executorEnv.PYTHONPATH /databricks/jars/rapids-4-spark_2.12-23.12.1.jar:/databricks/spark/python
       spark.sql.execution.arrow.maxRecordsPerBatch 100000
       spark.rapids.memory.gpu.minAllocFraction 0.0001
       spark.plugins com.nvidia.spark.SQLPlugin
diff --git a/notebooks/databricks/init-pip-cuda-11.8.sh b/notebooks/databricks/init-pip-cuda-11.8.sh
index b7b2169e..39fb0ac6 100644
--- a/notebooks/databricks/init-pip-cuda-11.8.sh
+++ b/notebooks/databricks/init-pip-cuda-11.8.sh
@@ -4,8 +4,8 @@ SPARK_RAPIDS_ML_ZIP=/dbfs/path/to/zip/file
 # IMPORTANT: specify RAPIDS_VERSION fully 23.10.0 and not 23.10
 # also in general, RAPIDS_VERSION (python) fields should omit any leading 0 in month/minor field (i.e. 23.8.0 and not 23.08.0)
 # while SPARK_RAPIDS_VERSION (jar) should have leading 0 in month/minor (e.g. 23.08.2 and not 23.8.2)
-RAPIDS_VERSION=23.10.0
-SPARK_RAPIDS_VERSION=23.10.0
+RAPIDS_VERSION=23.12.0
+SPARK_RAPIDS_VERSION=23.12.1
 
 curl -L https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/${SPARK_RAPIDS_VERSION}/rapids-4-spark_2.12-${SPARK_RAPIDS_VERSION}-cuda11.jar -o /databricks/jars/rapids-4-spark_2.12-${SPARK_RAPIDS_VERSION}.jar
 
diff --git a/notebooks/dataproc/README.md b/notebooks/dataproc/README.md
index 46208292..21a622dc 100644
--- a/notebooks/dataproc/README.md
+++ b/notebooks/dataproc/README.md
@@ -29,7 +29,7 @@ If you already have a Dataproc account, you can run the example notebooks on a D
 - Create a cluster with at least two single-gpu workers.  **Note**: in addition to the initialization script from above, this also uses the standard [initialization actions](https://github.com/GoogleCloudDataproc/initialization-actions) for installing the GPU drivers and RAPIDS:
   ```
   export CUDA_VERSION=11.8
-  export RAPIDS_VERSION=23.10.0
+  export RAPIDS_VERSION=23.12.0
 
   gcloud dataproc clusters create $USER-spark-rapids-ml \
   --image-version=2.1-ubuntu \
diff --git a/notebooks/dataproc/spark_rapids_ml.sh b/notebooks/dataproc/spark_rapids_ml.sh
index 5a860a60..d7690a93 100644
--- a/notebooks/dataproc/spark_rapids_ml.sh
+++ b/notebooks/dataproc/spark_rapids_ml.sh
@@ -1,6 +1,6 @@
 #!/bin/bash
 
-RAPIDS_VERSION=23.10.0
+RAPIDS_VERSION=23.12.0
 
 # patch existing packages
 mamba install "llvmlite<0.40,>=0.39.0dev0" "numba>=0.56.2"
diff --git a/notebooks/umap.ipynb b/notebooks/umap.ipynb
index b29f84a9..43c1f19e 100644
--- a/notebooks/umap.ipynb
+++ b/notebooks/umap.ipynb
@@ -652,7 +652,7 @@
     "import os\n",
     "import requests\n",
     "\n",
-    "SPARK_RAPIDS_VERSION = \"23.08.1\"\n",
+    "SPARK_RAPIDS_VERSION = \"23.12.1\"\n",
     "cuda_version = \"12\"\n",
     "rapids_jar = f\"rapids-4-spark_2.12-{SPARK_RAPIDS_VERSION}.jar\"\n",
     "\n",
diff --git a/python/README.md b/python/README.md
index dac24b9d..dcc6e339 100644
--- a/python/README.md
+++ b/python/README.md
@@ -8,9 +8,9 @@ For simplicity, the following instructions just use Spark local mode, assuming a
 
 First, install RAPIDS cuML per [these instructions](https://rapids.ai/start.html).   Example for CUDA Toolkit 11.8:
 ```bash
-conda create -n rapids-23.10 \
+conda create -n rapids-23.12 \
     -c rapidsai -c conda-forge -c nvidia \
-    cuml=23.10 python=3.9 cuda-version=11.8
+    cuml=23.12 python=3.9 cuda-version=11.8
 ```
 
 **Note**: while testing, we recommend using conda or docker to simplify installation and isolate your environment while experimenting.  Once you have a working environment, you can then try installing directly, if necessary.
@@ -19,7 +19,7 @@ conda create -n rapids-23.10 \
 
 Once you have the conda environment, activate it and install the required packages.
 ```bash
-conda activate rapids-23.10
+conda activate rapids-23.12
 
 ## for development access to notebooks, tests, and benchmarks
 git clone --branch main https://github.com/NVIDIA/spark-rapids-ml.git
diff --git a/python/benchmark/databricks/gpu_cluster_spec.sh b/python/benchmark/databricks/gpu_cluster_spec.sh
index f8bbc47f..e1f0a91d 100644
--- a/python/benchmark/databricks/gpu_cluster_spec.sh
+++ b/python/benchmark/databricks/gpu_cluster_spec.sh
@@ -9,7 +9,7 @@ cat <<EOF
         "spark.task.cpus": "1",
         "spark.databricks.delta.preview.enabled": "true",
         "spark.python.worker.reuse": "true",
-        "spark.executorEnv.PYTHONPATH": "/databricks/jars/rapids-4-spark_2.12-23.10.0.jar:/databricks/spark/python",
+        "spark.executorEnv.PYTHONPATH": "/databricks/jars/rapids-4-spark_2.12-23.12.1.jar:/databricks/spark/python",
         "spark.sql.files.minPartitionNum": "2",
         "spark.sql.execution.arrow.maxRecordsPerBatch": "10000",
         "spark.executor.cores": "8",
diff --git a/python/benchmark/databricks/init-pip-cuda-11.8.sh b/python/benchmark/databricks/init-pip-cuda-11.8.sh
index ef10f72d..0c3f3f02 100644
--- a/python/benchmark/databricks/init-pip-cuda-11.8.sh
+++ b/python/benchmark/databricks/init-pip-cuda-11.8.sh
@@ -4,9 +4,9 @@ SPARK_RAPIDS_ML_ZIP=/dbfs/path/to/spark-rapids-ml.zip
 BENCHMARK_ZIP=/dbfs/path/to/benchmark.zip
 # IMPORTANT: specify rapids fully 23.10.0 and not 23.10
 # also, in general, RAPIDS_VERSION (python) fields should omit any leading 0 in month/minor field (i.e. 23.8.0 and not 23.08.0)
-# while SPARK_RAPIDS_VERSION (jar) should have leading 0 in month/minor (e.g. 23.08.2 and not 23.8.1)
-RAPIDS_VERSION=23.10.0
-SPARK_RAPIDS_VERSION=23.10.0
+# while SPARK_RAPIDS_VERSION (jar) should have leading 0 in month/minor (e.g. 23.08.2 and not 23.8.2)
+RAPIDS_VERSION=23.12.0
+SPARK_RAPIDS_VERSION=23.12.1
 
 curl -L https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/${SPARK_RAPIDS_VERSION}/rapids-4-spark_2.12-${SPARK_RAPIDS_VERSION}-cuda11.jar -o /databricks/jars/rapids-4-spark_2.12-${SPARK_RAPIDS_VERSION}.jar
 
diff --git a/python/benchmark/dataproc/init_benchmark.sh b/python/benchmark/dataproc/init_benchmark.sh
index 7f854d0e..2c0d7f54 100755
--- a/python/benchmark/dataproc/init_benchmark.sh
+++ b/python/benchmark/dataproc/init_benchmark.sh
@@ -8,7 +8,7 @@ function get_metadata_attribute() {
   /usr/share/google/get_metadata_value "attributes/${attribute_name}" || echo -n "${default_value}"
 }
 
-RAPIDS_VERSION=$(get_metadata_attribute rapids-version 23.10.0)
+RAPIDS_VERSION=$(get_metadata_attribute rapids-version 23.12.0)
 
 # patch existing packages
 mamba install "llvmlite<0.40,>=0.39.0dev0" "numba>=0.56.2"
diff --git a/python/pyproject.toml b/python/pyproject.toml
index e8c3d4eb..37080c95 100644
--- a/python/pyproject.toml
+++ b/python/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "spark-rapids-ml"
-version = "23.10.0"
+version = "23.12.0"
 authors = [
   { name="Jinfeng Li", email="jinfeng@nvidia.com" },
   { name="Bobby Wang", email="bobwang@nvidia.com" },
diff --git a/python/run_benchmark.sh b/python/run_benchmark.sh
index 60e27804..6082bcae 100755
--- a/python/run_benchmark.sh
+++ b/python/run_benchmark.sh
@@ -99,7 +99,7 @@ EOF
 
 if [[ $cluster_type == "gpu_etl" ]]
 then
-SPARK_RAPIDS_VERSION=23.10.0
+SPARK_RAPIDS_VERSION=23.12.1
 rapids_jar=${rapids_jar:-rapids-4-spark_2.12-$SPARK_RAPIDS_VERSION.jar}
 if [ ! -f $rapids_jar ]; then
     echo "downloading spark rapids jar"