diff --git a/model/models/gemma3/model_text.go b/model/models/gemma3/model_text.go
index 70d7797e9..f13053417 100644
--- a/model/models/gemma3/model_text.go
+++ b/model/models/gemma3/model_text.go
@@ -86,12 +86,6 @@ func (sa *TextSelfAttention) Forward(ctx ml.Context, layer int, hiddenState, pos
 	q = sa.QueryNorm.Forward(ctx, q, opts.eps)
 	q = fast.RoPE(ctx, q, positionIDs, opts.attnKeyLen, ropeBase, opts.ropeScale, rope.WithTypeNeoX())
 
-	if opts.largeModelScaling {
-		q = q.Scale(ctx, 1.0/math.Sqrt(float64(opts.hiddenSize/opts.numHeads)))
-	} else {
-		q = q.Scale(ctx, 1.0/math.Sqrt(float64(opts.attnKeyLen)))
-	}
-
 	k := sa.Key.Forward(ctx, hiddenState)
 	k = k.Reshape(ctx, opts.attnKeyLen, opts.numKVHeads, batchSize)
 	k = sa.KeyNorm.Forward(ctx, k, opts.eps)
@@ -100,8 +94,12 @@ func (sa *TextSelfAttention) Forward(ctx ml.Context, layer int, hiddenState, pos
 	v := sa.Value.Forward(ctx, hiddenState)
 	v = v.Reshape(ctx, opts.attnValLen, opts.numKVHeads, batchSize)
 
-	scaleFactor := 1.0
-	kqv := nn.Attention(ctx, q, k, v, scaleFactor, cache)
+	scale := 1.0 / math.Sqrt(float64(opts.attnKeyLen))
+	if opts.largeModelScaling {
+		scale = 1.0 / math.Sqrt(float64(opts.hiddenSize/opts.numHeads))
+	}
+
+	kqv := nn.Attention(ctx, q, k, v, scale, cache)
 	kqv = kqv.Reshape(ctx, opts.attnValLen*opts.numHeads, batchSize)
 
 	return sa.Output.Forward(ctx, kqv)