diff --git a/python/taichi/linalg/sparse_matrix.py b/python/taichi/linalg/sparse_matrix.py
index 443afd933aae3..691f76b1cb912 100644
--- a/python/taichi/linalg/sparse_matrix.py
+++ b/python/taichi/linalg/sparse_matrix.py
@@ -284,12 +284,12 @@ def build(self, dtype=f32, _format="CSR"):
         taichi_arch = get_runtime().prog.config().arch
         if taichi_arch in [_ti_core.Arch.x64, _ti_core.Arch.arm64]:
             sm = self.ptr.build()
-            return SparseMatrix(sm=sm, dtype=dtype)
+            return SparseMatrix(sm=sm, dtype=self.dtype)
         if taichi_arch == _ti_core.Arch.cuda:
-            if dtype != f32:
+            if self.dtype != f32:
                 raise TaichiRuntimeError("CUDA sparse matrix only supports f32.")
             sm = self.ptr.build_cuda()
-            return SparseMatrix(sm=sm, dtype=dtype)
+            return SparseMatrix(sm=sm, dtype=self.dtype)
         raise TaichiRuntimeError("Sparse matrix only supports CPU and CUDA backends.")
 
 
diff --git a/python/taichi/linalg/sparse_solver.py b/python/taichi/linalg/sparse_solver.py
index 05775c0dda496..3850cbee227f4 100644
--- a/python/taichi/linalg/sparse_solver.py
+++ b/python/taichi/linalg/sparse_solver.py
@@ -21,6 +21,7 @@ class SparseSolver:
 
     def __init__(self, dtype=f32, solver_type="LLT", ordering="AMD"):
         self.matrix = None
+        self.dtype = dtype
         solver_type_list = ["LLT", "LDLT", "LU"]
         solver_ordering = ["AMD", "COLAMD"]
         if solver_type in solver_type_list and ordering in solver_ordering:
@@ -70,6 +71,10 @@ def analyze_pattern(self, sparse_matrix):
         """
         if isinstance(sparse_matrix, SparseMatrix):
             self.matrix = sparse_matrix
+            if self.matrix.dtype != self.dtype:
+                raise TaichiRuntimeError(
+                    f"The SparseSolver's dtype {self.dtype} is not consistent with the SparseMatrix's dtype {self.matrix.dtype}."
+                )
             self.solver.analyze_pattern(sparse_matrix.matrix)
         else:
             self._type_assert(sparse_matrix)