diff --git a/ci/Dockerfile b/ci/Dockerfile
index 517bc773..43cc1f5c 100644
--- a/ci/Dockerfile
+++ b/ci/Dockerfile
@@ -38,5 +38,5 @@ RUN wget --quiet https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86
 
 # install cuML
 ARG CUML_VER=24.12
-RUN conda install -y -c rapidsai-nightly -c conda-forge -c nvidia cuml=$CUML_VER cuvs=$CUML_VER python=3.10 cuda-version=11.8 numpy~=1.0 \
+RUN conda install -y -c rapidsai -c conda-forge -c nvidia cuml=$CUML_VER cuvs=$CUML_VER python=3.10 cuda-version=11.8 numpy~=1.0 \
     && conda clean --all -f -y
diff --git a/docker/Dockerfile.pip b/docker/Dockerfile.pip
index 19146ab0..4d5c65bc 100644
--- a/docker/Dockerfile.pip
+++ b/docker/Dockerfile.pip
@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2023, NVIDIA CORPORATION.
+# Copyright (c) 2024, NVIDIA CORPORATION.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -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=24.10.0
+ARG RAPIDS_VERSION=24.12.0
 ARG ARCH=amd64
 #ARG ARCH=arm64
 # Install packages to build spark-rapids-ml
diff --git a/docker/Dockerfile.python b/docker/Dockerfile.python
index b304cd38..6e00dd9a 100644
--- a/docker/Dockerfile.python
+++ b/docker/Dockerfile.python
@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2023, NVIDIA CORPORATION.
+# Copyright (c) 2024, NVIDIA CORPORATION.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -17,7 +17,7 @@
 ARG CUDA_VERSION=11.8.0
 FROM nvidia/cuda:${CUDA_VERSION}-devel-ubuntu20.04
 
-ARG CUML_VERSION=24.10
+ARG CUML_VERSION=24.12
 
 # Install packages to build spark-rapids-ml
 RUN apt update -y \
diff --git a/notebooks/aws-emr/init-bootstrap-action.sh b/notebooks/aws-emr/init-bootstrap-action.sh
index 096b4d94..16def3b4 100755
--- a/notebooks/aws-emr/init-bootstrap-action.sh
+++ b/notebooks/aws-emr/init-bootstrap-action.sh
@@ -27,7 +27,7 @@ sudo bash -c "wget https://www.python.org/ftp/python/3.10.9/Python-3.10.9.tgz &&
 tar xzf Python-3.10.9.tgz && cd Python-3.10.9 && \
 ./configure --enable-optimizations && make altinstall"
 
-RAPIDS_VERSION=24.10.0
+RAPIDS_VERSION=24.12.0
 
 sudo /usr/local/bin/pip3.10 install --upgrade pip
 
diff --git a/notebooks/databricks/README.md b/notebooks/databricks/README.md
index 1d60a204..7b5cadf6 100644
--- a/notebooks/databricks/README.md
+++ b/notebooks/databricks/README.md
@@ -51,7 +51,7 @@ 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_2.12-24.08.1.jar:/databricks/spark/python
+      spark.executorEnv.PYTHONPATH /databricks/jars/rapids-4-spark_2.12-24.10.1.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 72ee582f..d3a7b9ed 100644
--- a/notebooks/databricks/init-pip-cuda-11.8.sh
+++ b/notebooks/databricks/init-pip-cuda-11.8.sh
@@ -18,8 +18,8 @@ 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=24.10.0
-SPARK_RAPIDS_VERSION=24.08.1
+RAPIDS_VERSION=24.12.0
+SPARK_RAPIDS_VERSION=24.10.1
 
 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 5051e581..55317eda 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=24.10.0
+  export RAPIDS_VERSION=24.12.0
 
   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 2810cee9..3ff07286 100644
--- a/notebooks/dataproc/spark_rapids_ml.sh
+++ b/notebooks/dataproc/spark_rapids_ml.sh
@@ -14,7 +14,7 @@
 # limitations under the License.
 
 
-RAPIDS_VERSION=24.10.0
+RAPIDS_VERSION=24.12.0
 
 # patch existing packages
 mamba install "llvmlite<0.40,>=0.39.0dev0" "numba>=0.56.2"
diff --git a/python/README.md b/python/README.md
index b2e495f8..71f6c422 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-24.10 \
+conda create -n rapids-24.12 \
     -c rapidsai -c conda-forge -c nvidia \
-    cuml=24.10 cuvs=24.10 python=3.10 cuda-version=11.8 numpy~=1.0
+    cuml=24.12 cuvs=24.12 python=3.10 cuda-version=11.8 numpy~=1.0
 ```
 
 **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-24.10 \
 
 Once you have the conda environment, activate it and install the required packages.
 ```bash
-conda activate rapids-24.10
+conda activate rapids-24.12
 
 ## 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/init-pip-cuda-11.8.sh b/python/benchmark/databricks/init-pip-cuda-11.8.sh
index 606618f8..e74fa213 100644
--- a/python/benchmark/databricks/init-pip-cuda-11.8.sh
+++ b/python/benchmark/databricks/init-pip-cuda-11.8.sh
@@ -19,7 +19,7 @@ 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 23.8.2)
-RAPIDS_VERSION=24.10.0
+RAPIDS_VERSION=24.12.0
 SPARK_RAPIDS_VERSION=24.10.1
 
 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-${SPARK_RAPIDS_VERSION}.jar
diff --git a/python/benchmark/dataproc/init_benchmark.sh b/python/benchmark/dataproc/init_benchmark.sh
index fc61cda1..27ece2d9 100755
--- a/python/benchmark/dataproc/init_benchmark.sh
+++ b/python/benchmark/dataproc/init_benchmark.sh
@@ -22,7 +22,7 @@ function get_metadata_attribute() {
   /usr/share/google/get_metadata_value "attributes/${attribute_name}" || echo -n "${default_value}"
 }
 
-RAPIDS_VERSION=$(get_metadata_attribute rapids-version 24.10.0)
+RAPIDS_VERSION=$(get_metadata_attribute rapids-version 24.12.0)
 
 # patch existing packages
 mamba install "llvmlite<0.40,>=0.39.0dev0" "numba>=0.56.2"