diff --git a/src/host/linalg.jl b/src/host/linalg.jl
index a873f48f..c9bbadbd 100644
--- a/src/host/linalg.jl
+++ b/src/host/linalg.jl
@@ -525,7 +525,8 @@ end
 ## matrix multiplication
 
 # GPU-backed members of Base's StridedArray union match LinearAlgebra's BLAS methods,
-# but cannot be converted to host pointers. Route them to the generic GPU kernels.
+# but cannot be converted to host pointers. Route them to the generic GPU kernels, or to the
+# storage-level `mul!` methods where the back-end can take them (see `strided_view_matmatmul!`).
 const StridedGPUSubArray{T,N} = Base.StridedSubArray{T,N,<:AbstractGPUArray}
 const AnyStridedGPUArray{T,N} = Union{AbstractGPUArray{T,N},StridedGPUSubArray{T,N}}
 const AnyStridedGPUVector{T} = AnyStridedGPUArray{T,1}
@@ -546,6 +547,26 @@ const AnyStridedGPUVecOrMatOperand{T} = Union{
 has_strided_gpu_view(As...) =
     any(A -> LinearAlgebra._unwrap(A) isa StridedGPUSubArray, As)
 
+# Back-ends overload the storage-level `mul!` to call their vendor library. Their gemm wrappers
+# accept views, but some pass `stride(X, 2)` as the leading dimension without validating the
+# layout, so only forward views that are valid BLAS operands: unit row stride and a leading
+# dimension of at least the number of rows (which rules out reversed columns). Not every
+# back-end checks dimensions either, so leave mismatches to the generic kernel to report.
+# Symmetric and Hermitian operands and products with a vector keep the generic kernels, as not
+# every back-end accepts views for those.
+blas_compatible(X) =
+    X isa AbstractMatrix && stride(X, 1) == 1 && stride(X, 2) >= max(1, size(X, 1))
+
+function strided_view_matmatmul!(C, A, B, a, b)
+    tA, tB = LinearAlgebra.wrapper_char(A), LinearAlgebra.wrapper_char(B)
+    pA, pB = LinearAlgebra._unwrap(A), LinearAlgebra._unwrap(B)
+    if tA in ('N', 'T', 'C') && tB in ('N', 'T', 'C') && all(blas_compatible, (C, pA, pB)) &&
+       size(A, 2) == size(B, 1) && size(C) == (size(A, 1), size(B, 2))
+        return LinearAlgebra.mul!(C, tA, tB, pA, pB, a, b)
+    end
+    return generic_matmatmul!(C, A, B, a, b)
+end
+
 # Intercept before LinearAlgebra unwraps operands and dispatches to backend BLAS methods. The
 # signatures also cover view-free products to avoid overlapping methods for each possible view
 # position; those calls are sent back through LinearAlgebra's original implementation.
@@ -564,7 +585,7 @@ end
 @inline function LinearAlgebra.mul!(C::AnyStridedGPUMatrix, A::AnyStridedGPUVecOrMatOperand,
                             B::AnyStridedGPUVecOrMatOperand, a::Number, b::Number)
     if has_strided_gpu_view(C, A, B)
-        return generic_matmatmul!(C, A, B, a, b)
+        return strided_view_matmatmul!(C, A, B, a, b)
     end
     invoke(LinearAlgebra.mul!,
            Tuple{AbstractMatrix,LinearAlgebra.AbstractVecOrMat,
@@ -587,7 +608,7 @@ end
 @inline function LinearAlgebra._mul!(C::AnyStridedGPUMatrix, A::AnyStridedGPUVecOrMatOperand,
                              B::AnyStridedGPUVecOrMatOperand, a::Number, b::Number)
     if has_strided_gpu_view(C, A, B)
-        return generic_matmatmul!(C, A, B, a, b)
+        return strided_view_matmatmul!(C, A, B, a, b)
     end
     invoke(LinearAlgebra._mul!,
            Tuple{AbstractMatrix,LinearAlgebra.AbstractVecOrMat,
diff --git a/test/testsuite/linalg.jl b/test/testsuite/linalg.jl
index d1a0e1c2..23251cdf 100644
--- a/test/testsuite/linalg.jl
+++ b/test/testsuite/linalg.jl
@@ -763,12 +763,25 @@ end
             C
         end
 
+        # reversed columns (negative stride along the second dimension)
+        @test compare((A, B) -> view(A, :, 6:-1:1) * view(B, 6:-1:1, :), AT, As, Bs)
+        @test compare((A, B) -> A * view(B, :, 10:-1:1), AT, As, Bs)
+        @test compare(A -> view(A, :, 6:-1:1)' * A, AT, As)
+        Cr = rand(T, 8, 10)
+        @test compare(AT, Cr, As, Bs) do C, A, B
+            mul!(view(C, :, 10:-1:1), A, B, T(2), T(1))
+            C
+        end
+
         # strided destination with contiguous operands
         B3 = rand(T, 3, 5)
         @test compare(AT, C, A2, B3) do C, A, B
             mul!(view(C, 1:2, :), A, B)
             C
         end
+
+        # mismatched destination
+        @test_throws DimensionMismatch mul!(AT(rand(T, 1, 5)), view(AT(A), 1:2, :), AT(B3))
     end
 
     if Float32 in eltypes && ComplexF32 in eltypes