diff --git a/sentence_transformers/losses/CachedGISTEmbedLoss.py b/sentence_transformers/losses/CachedGISTEmbedLoss.py
index e8e131582..51bc1c02b 100644
--- a/sentence_transformers/losses/CachedGISTEmbedLoss.py
+++ b/sentence_transformers/losses/CachedGISTEmbedLoss.py
@@ -265,7 +265,7 @@ def calculate_loss_and_cache_gradients(self, reps: list[list[Tensor]], reps_guid
             # Apply thresholds based on guided model similarities
             ap_sim[guided_ap_sim > guided_sim] = -torch.inf
             aa_sim[guided_aa_sim > guided_sim] = -torch.inf
-            pp_sim[guided_pp_sim > guided_sim] = -torch.inf
+            pp_sim[guided_pp_sim >= guided_sim] = -torch.inf
 
             # Concatenate the similarity matrices for anchor-positive, anchor-anchor, and positive-positive
             scores = torch.cat([ap_sim, aa_sim, pp_sim], dim=1)
@@ -328,7 +328,7 @@ def calculate_loss(self, reps: list[list[Tensor]], reps_guided: list[list[Tensor
             # Apply thresholds based on guided model similarities
             ap_sim[guided_ap_sim > guided_sim] = -torch.inf
             aa_sim[guided_aa_sim > guided_sim] = -torch.inf
-            pp_sim[guided_pp_sim > guided_sim] = -torch.inf
+            pp_sim[guided_pp_sim >= guided_sim] = -torch.inf
 
             # Concatenate the similarity matrices for anchor-positive, anchor-anchor, and positive-positive
             scores = torch.cat([ap_sim, aa_sim, pp_sim], dim=1)
diff --git a/sentence_transformers/losses/GISTEmbedLoss.py b/sentence_transformers/losses/GISTEmbedLoss.py
index 5111b2b0c..4b79b39f6 100644
--- a/sentence_transformers/losses/GISTEmbedLoss.py
+++ b/sentence_transformers/losses/GISTEmbedLoss.py
@@ -150,7 +150,7 @@ def forward(self, sentence_features: Iterable[dict[str, Tensor]], labels: Tensor
         # the loss.
         ap_sim[guided_ap_sim > guided_sim] = -torch.inf
         aa_sim[guided_aa_sim > guided_sim] = -torch.inf
-        pp_sim[guided_pp_sim > guided_sim] = -torch.inf
+        pp_sim[guided_pp_sim >= guided_sim] = -torch.inf
 
         scores = [ap_sim, aa_sim, pp_sim]