diff --git a/x/models/nn/nn.go b/x/models/nn/nn.go
index 9aa333bc..7c7461f0 100644
--- a/x/models/nn/nn.go
+++ b/x/models/nn/nn.go
@@ -61,6 +61,9 @@ type Linear struct {
 }
 
 func NewLinear(weight *mlx.Array, bias *mlx.Array) *Linear {
+	if bias != nil && bias.Valid() && bias.DType() != weight.DType() {
+		bias = bias.AsType(weight.DType())
+	}
 	return &Linear{Weight: weight, Bias: bias}
 }
 
@@ -95,6 +98,9 @@ func NewQuantizedLinear(weight *mlx.Array, bias *mlx.Array, groupSize, bits int,
 	} else {
 		mlx.Eval(qw, scales)
 	}
+	if bias != nil && bias.Valid() && bias.DType() != weight.DType() {
+		bias = bias.AsType(weight.DType())
+	}
 	return &QuantizedLinear{
 		Weight:    qw,
 		Scales:    scales,
@@ -107,20 +113,22 @@ func NewQuantizedLinear(weight *mlx.Array, bias *mlx.Array, groupSize, bits int,
 }
 
 func (ql *QuantizedLinear) Forward(x *mlx.Array) *mlx.Array {
-	var out *mlx.Array
+	out := mlx.QuantizedMatmul(x, ql.Weight, ql.Scales, ql.QBiases, true, ql.GroupSize, ql.Bits, ql.Mode)
 	if ql.GlobalScale != nil {
 		// Double-scale nvfp4 (e.g., NVIDIA ModelOpt): standard quantized_matmul
 		// followed by global_scale multiply. The global_scale is a per-tensor
 		// F32 scalar (weight_scale_2 in NVIDIA's format).
 		// TODO: switch to a fused double-scale matmul once MLX has kernel
 		// coverage for this path.
-		out = mlx.QuantizedMatmul(x, ql.Weight, ql.Scales, ql.QBiases, true, ql.GroupSize, ql.Bits, ql.Mode)
-		out = mlx.Mul(out, ql.GlobalScale)
-	} else {
-		out = mlx.QuantizedMatmul(x, ql.Weight, ql.Scales, ql.QBiases, true, ql.GroupSize, ql.Bits, ql.Mode)
+		outDType := out.DType()
+		out = mlx.Mul(out, ql.GlobalScale).AsType(outDType)
 	}
 	if ql.Bias != nil && ql.Bias.Valid() {
-		out = out.Add(ql.Bias)
+		bias := ql.Bias
+		if bias.DType() != out.DType() {
+			bias = bias.AsType(out.DType())
+		}
+		out = out.Add(bias)
 	}
 	return out
 }
@@ -184,7 +192,8 @@ func (qe *QuantizedEmbedding) Forward(indices *mlx.Array) *mlx.Array {
 	}
 	out := mlx.Dequantize(weight, scales, qbiases, qe.GroupSize, qe.Bits, qe.Mode)
 	if qe.GlobalScale != nil {
-		out = mlx.Mul(out, qe.GlobalScale)
+		outDType := out.DType()
+		out = mlx.Mul(out, qe.GlobalScale).AsType(outDType)
 	}
 	return out
 }