diff --git a/flax/linen/fp8_ops.py b/flax/linen/fp8_ops.py
index a1fc39a673..e4b368e72d 100644
--- a/flax/linen/fp8_ops.py
+++ b/flax/linen/fp8_ops.py
@@ -12,9 +12,10 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import warnings
 from functools import partial
 
-from jax import custom_vjp, lax, random
+from jax import custom_jvp, custom_vjp, lax, random
 from jax import numpy as jnp
 
 from flax.linen import initializers, module
@@ -120,6 +121,39 @@ def out_qdq_bwd(compute_dtype, res, g):
 out_qdq.defvjp(out_qdq_fwd, out_qdq_bwd)
 
 
+@partial(custom_jvp, nondiff_argnums=(2, 3, 4))
+def dot_general_with_precision(
+  lhs, rhs, dimension_numbers, precision=None, preferred_element_type=None
+):
+  if precision != None or preferred_element_type != None:
+    warnings.warn(
+      'The function dot_general_with_precision will set the '
+      'precision/preferred_element_type and disregard any provided '
+      'values.'
+    )
+  return lax.dot_general(
+    lhs, rhs, dimension_numbers, precision=lax.Precision.DEFAULT
+  )
+
+
+@dot_general_with_precision.defjvp
+def dot_general_with_precision_jvp(
+  dimension_numbers, precision, preferred_element_type, primals, tangents
+):
+  lhs, rhs = primals
+  lhs_dot, rhs_dot = tangents
+
+  out = lax.dot_general(
+    lhs, rhs, dimension_numbers, precision=lax.Precision.DEFAULT
+  )
+  grad_out = lax.dot_general(
+    lhs_dot, rhs, dimension_numbers, precision=lax.Precision.HIGHEST
+  ) + lax.dot_general(
+    lhs, rhs_dot, dimension_numbers, precision=lax.Precision.HIGHEST
+  )
+  return out, grad_out
+
+
 class Fp8DotGeneralOp(module.Module):
   amax_history_length: int = 1024
 
@@ -162,7 +196,6 @@ def __call__(self, *args, **kwargs):
     x = args[0]
     k = args[1]
     dimension_numbers = args[2]
-    precision = kwargs['precision']
 
     # Use the `k.dtype` since it aligns with the `dtype` of its layers,
     # namely, the computation data type.
@@ -175,7 +208,7 @@ def __call__(self, *args, **kwargs):
     k_qdq = in_qdq(
       comp_dtype, k, self.kernel_scale.value, self.kernel_amax_history.value
     )
-    y_qdq = lax.dot_general(x_qdq, k_qdq, dimension_numbers, precision)  # type: ignore
+    y_qdq = dot_general_with_precision(x_qdq, k_qdq, dimension_numbers)  # type: ignore
     y = out_qdq(
       comp_dtype,
       y_qdq,