diff --git a/.azure-pipelines/azure-pipelines-benchmarks.yml b/.azure-pipelines/azure-pipelines-benchmarks.yml
index 412b926f84..91b1e08b8b 100644
--- a/.azure-pipelines/azure-pipelines-benchmarks.yml
+++ b/.azure-pipelines/azure-pipelines-benchmarks.yml
@@ -29,7 +29,7 @@ jobs:
       python -m pip install wheel
       python -m pip install --no-cache-dir -r requirements.txt
       python -m pip install --no-cache-dir -r requirements-optional.txt
-      python -m pip install asv!=0.6.2
+      python -m pip install asv==0.6.1
     displayName: 'Install requirements'
 
   - script: |
diff --git a/CHANGELOG.md b/CHANGELOG.md
index d25dfa5ace..a5b807ff4c 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -6,8 +6,8 @@
 
 ### Maintenance and fixes
 - Fix deprecations introduced in latest pandas and xarray versions, and prepare for numpy 2.0 ones ([2315](https://github.com/arviz-devs/arviz/pull/2315)))
-
--   Refactor ECDF code ([2311](https://github.com/arviz-devs/arviz/pull/2311))
+- Refactor ECDF code ([2311](https://github.com/arviz-devs/arviz/pull/2311))
+- Fix `plot_forest` when Numba is installed ([2319](https://github.com/arviz-devs/arviz/pull/2319))
 
 ### Deprecation
 
diff --git a/arviz/data/inference_data.py b/arviz/data/inference_data.py
index 3740fca1e0..c921c0a9dd 100644
--- a/arviz/data/inference_data.py
+++ b/arviz/data/inference_data.py
@@ -254,8 +254,7 @@ def __len__(self) -> int:
 
     def __iter__(self) -> Iterator[str]:
         """Iterate over groups in InferenceData object."""
-        for group in self._groups_all:
-            yield group
+        yield from self._groups_all
 
     def __contains__(self, key: object) -> bool:
         """Return True if the named item is present, and False otherwise."""
diff --git a/arviz/data/io_pystan.py b/arviz/data/io_pystan.py
index 0b899c5e9d..480a1be638 100644
--- a/arviz/data/io_pystan.py
+++ b/arviz/data/io_pystan.py
@@ -676,8 +676,7 @@ def get_draws(fit, variables=None, ignore=None, warmup=False, dtypes=None):
         for item in par_keys:
             _, shape = item.replace("]", "").split("[")
             shape_idx_min = min(int(shape_value) for shape_value in shape.split(","))
-            if shape_idx_min < shift:
-                shift = shape_idx_min
+            shift = min(shift, shape_idx_min)
         # If shift is higher than 1, this will probably mean that Stan
         # has implemented sparse structure (saves only non-zero parts),
         # but let's hope that dims are still corresponding to the full shape
diff --git a/arviz/plots/backends/bokeh/forestplot.py b/arviz/plots/backends/bokeh/forestplot.py
index 9406641fbe..467aa44718 100644
--- a/arviz/plots/backends/bokeh/forestplot.py
+++ b/arviz/plots/backends/bokeh/forestplot.py
@@ -15,7 +15,6 @@
 from ....stats import hdi
 from ....stats.density_utils import get_bins, histogram, kde
 from ....stats.diagnostics import _ess, _rhat
-from ....utils import conditional_jit
 from ...plot_utils import _scale_fig_size
 from .. import show_layout
 from . import backend_kwarg_defaults
@@ -277,7 +276,6 @@ def labels_and_ticks(self):
         """Collect labels and ticks from plotters."""
         val = self.plotters.values()
 
-        @conditional_jit(forceobj=True, nopython=False)
         def label_idxs():
             labels, idxs = [], []
             for plotter in val:
diff --git a/arviz/plots/backends/matplotlib/forestplot.py b/arviz/plots/backends/matplotlib/forestplot.py
index 67b710bf48..3993f497e6 100644
--- a/arviz/plots/backends/matplotlib/forestplot.py
+++ b/arviz/plots/backends/matplotlib/forestplot.py
@@ -11,7 +11,6 @@
 from ....stats.density_utils import get_bins, histogram, kde
 from ....stats.diagnostics import _ess, _rhat
 from ....sel_utils import xarray_var_iter
-from ....utils import conditional_jit
 from ...plot_utils import _scale_fig_size
 from . import backend_kwarg_defaults, backend_show
 
@@ -236,7 +235,6 @@ def labels_and_ticks(self):
         """Collect labels and ticks from plotters."""
         val = self.plotters.values()
 
-        @conditional_jit(forceobj=True, nopython=False)
         def label_idxs():
             labels, idxs = [], []
             for plotter in val: