diff --git a/gtsam/hybrid/HybridGaussianConditional.cpp b/gtsam/hybrid/HybridGaussianConditional.cpp
index d0f812d73..5e80f802a 100644
--- a/gtsam/hybrid/HybridGaussianConditional.cpp
+++ b/gtsam/hybrid/HybridGaussianConditional.cpp
@@ -62,21 +62,6 @@ struct HybridGaussianConditional::ConstructorHelper {
     }
   }
 
-  /// Construct from means and a single sigma.
-  ConstructorHelper(Key x, const DiscreteKey mode,
-                    const std::vector<Vector> &means, double sigma)
-      : nrFrontals(1), minNegLogConstant(0) {
-    std::vector<GaussianConditional::shared_ptr> gcs;
-    for (const auto &mean : means) {
-      auto c = GaussianConditional::sharedMeanAndStddev(x, mean, sigma);
-      gcs.push_back(c);
-    }
-    conditionals = Conditionals({mode}, gcs);
-    pairs = FactorValuePairs(conditionals, [](const auto &c) {
-      return GaussianFactorValuePair{c, 0.0};
-    });
-  }
-
   /// Construct from means and a sigmas.
   ConstructorHelper(Key x, const DiscreteKey mode,
                     const std::vector<std::pair<Vector, double>> &parameters)
@@ -110,12 +95,6 @@ HybridGaussianConditional::HybridGaussianConditional(
     : HybridGaussianConditional(DiscreteKeys{mode},
                                 Conditionals({mode}, conditionals)) {}
 
-HybridGaussianConditional::HybridGaussianConditional(
-    Key x, const DiscreteKey mode, const std::vector<Vector> &means,
-    double sigma)
-    : HybridGaussianConditional(DiscreteKeys{mode},
-                                ConstructorHelper(x, mode, means, sigma)) {}
-
 HybridGaussianConditional::HybridGaussianConditional(
     Key x, const DiscreteKey mode,
     const std::vector<std::pair<Vector, double>> &parameters)
diff --git a/gtsam/hybrid/HybridGaussianConditional.h b/gtsam/hybrid/HybridGaussianConditional.h
index 662318837..79cafece7 100644
--- a/gtsam/hybrid/HybridGaussianConditional.h
+++ b/gtsam/hybrid/HybridGaussianConditional.h
@@ -87,17 +87,6 @@ class GTSAM_EXPORT HybridGaussianConditional
       const DiscreteKey &mode,
       const std::vector<GaussianConditional::shared_ptr> &conditionals);
 
-  /**
-   * @brief Construct from vector of means and a single sigma.
-   *
-   * @param x The continuous key.
-   * @param mode The discrete key.
-   * @param means The means for the Gaussian conditionals.
-   * @param sigma The standard deviation for the Gaussian conditionals.
-   */
-  HybridGaussianConditional(Key x, const DiscreteKey mode,
-                            const std::vector<Vector> &means, double sigma);
-
   /**
    * @brief Construct from vector of means and sigmas.
    *
diff --git a/gtsam/hybrid/tests/testGaussianMixture.cpp b/gtsam/hybrid/tests/testGaussianMixture.cpp
index 87ef5e25d..7d227f2d7 100644
--- a/gtsam/hybrid/tests/testGaussianMixture.cpp
+++ b/gtsam/hybrid/tests/testGaussianMixture.cpp
@@ -80,8 +80,9 @@ TEST(GaussianMixture, GaussianMixtureModel) {
   double sigma = 2.0;
 
   HybridBayesNet hbn;
-  std::vector<Vector> means{Vector1(mu0), Vector1(mu1)};
-  hbn.emplace_shared<HybridGaussianConditional>(Z(0), m, means, sigma);
+  std::vector<std::pair<Vector, double>> parameters{{Vector1(mu0), sigma},
+                                                    {Vector1(mu1), sigma}};
+  hbn.emplace_shared<HybridGaussianConditional>(Z(0), m, parameters);
   hbn.push_back(mixing);
 
   // At the halfway point between the means, we should get P(m|z)=0.5