diff --git a/README.md b/README.md
index 8d1ecc8..b893842 100644
--- a/README.md
+++ b/README.md
@@ -15,14 +15,14 @@ The goal of model-based optimization is to find an input **x** that maximizes an
 Design-Bench can be installed with the complete set of benchmarks via our pip package.
 
 ```bash
-pip install design-bench[all]==2.0.13
+pip install design-bench[all]==2.0.14
 pip install morphing-agents==1.5.1
 ```
 
 Alternatively, if you do not have MuJoCo, you may opt for a minimal install.
 
 ```bash
-pip install design-bench==2.0.13
+pip install design-bench==2.0.14
 ```
 
 ## Available Tasks
diff --git a/setup.py b/setup.py
index 5e89361..5854ec8 100644
--- a/setup.py
+++ b/setup.py
@@ -7,7 +7,7 @@
     LONG_DESCRIPTION = readme.read()
 
 
-setup(name='design-bench', version='2.0.13', license='MIT',
+setup(name='design-bench', version='2.0.14', license='MIT',
       packages=find_packages(include=['design_bench', 'design_bench.*']),
       description='Design-Bench: Benchmarks for '
                   'Data-Driven Offline Model-Based Optimization',
@@ -17,7 +17,7 @@
       author_email='brandon@btrabucco.com',
       url='https://github.com/brandontrabucco/design-bench',
       download_url='https://github.com/'
-                   'brandontrabucco/design-bench/archive/v2_0_13.tar.gz',
+                   'brandontrabucco/design-bench/archive/v2_0_14.tar.gz',
       keywords=['Deep Learning', 'Neural Networks',
                 'Benchmark', 'Model-Based Optimization'],
       extras_require={'all': ['gym[mujoco]'], 'cma': ['cma']},