diff --git a/mat/cholesky.go b/mat/cholesky.go
index e6530fd2..d95533cf 100644
--- a/mat/cholesky.go
+++ b/mat/cholesky.go
@@ -207,29 +207,34 @@ func (a *Cholesky) SolveChol(m *Dense, b *Cholesky) error {
 
 // SolveVec finds the vector v that solves A * v = b where A is represented
 // by the Cholesky decomposition, placing the result in v.
-func (c *Cholesky) SolveVec(v, b *VecDense) error {
+func (c *Cholesky) SolveVec(v *VecDense, b Vector) error {
 	if !c.valid() {
 		panic(badCholesky)
 	}
 	n := c.chol.mat.N
-	vn := b.Len()
-	if vn != n {
+	if br, bc := b.Dims(); br != n || bc != 1 {
 		panic(ErrShape)
 	}
-	if v != b {
-		v.checkOverlap(b.mat)
+	switch rv := b.(type) {
+	default:
+		v.reuseAs(n)
+		return c.Solve(v.asDense(), b)
+	case RawVectorer:
+		bmat := rv.RawVector()
+		if v != b {
+			v.checkOverlap(bmat)
+		}
+		v.reuseAs(n)
+		if v != b {
+			v.CopyVec(b)
+		}
+		blas64.Trsv(blas.Trans, c.chol.mat, v.mat)
+		blas64.Trsv(blas.NoTrans, c.chol.mat, v.mat)
+		if c.cond > ConditionTolerance {
+			return Condition(c.cond)
+		}
+		return nil
 	}
-	v.reuseAs(n)
-	if v != b {
-		v.CopyVec(b)
-	}
-	blas64.Trsv(blas.Trans, c.chol.mat, v.mat)
-	blas64.Trsv(blas.NoTrans, c.chol.mat, v.mat)
-	if c.cond > ConditionTolerance {
-		return Condition(c.cond)
-	}
-	return nil
-
 }
 
 // RawU returns the Triangular matrix used to store the Cholesky decomposition of
diff --git a/mat/lq.go b/mat/lq.go
index c8b797a6..bc7eb95d 100644
--- a/mat/lq.go
+++ b/mat/lq.go
@@ -209,17 +209,27 @@ func (lq *LQ) Solve(m *Dense, trans bool, b Matrix) error {
 
 // SolveVec finds a minimum-norm solution to a system of linear equations.
 // Please see LQ.Solve for the full documentation.
-func (lq *LQ) SolveVec(v *VecDense, trans bool, b *VecDense) error {
-	if v != b {
-		v.checkOverlap(b.mat)
-	}
+func (lq *LQ) SolveVec(v *VecDense, trans bool, b Vector) error {
 	r, c := lq.lq.Dims()
+	if _, bc := b.Dims(); bc != 1 {
+		panic(ErrShape)
+	}
+
 	// The Solve implementation is non-trivial, so rather than duplicate the code,
 	// instead recast the VecDenses as Dense and call the matrix code.
+	bm := Matrix(b)
+	if rv, ok := b.(RawVectorer); ok {
+		bmat := rv.RawVector()
+		if v != b {
+			v.checkOverlap(bmat)
+		}
+		b := VecDense{mat: bmat, n: b.Len()}
+		bm = b.asDense()
+	}
 	if trans {
 		v.reuseAs(r)
 	} else {
 		v.reuseAs(c)
 	}
-	return lq.Solve(v.asDense(), trans, b.asDense())
+	return lq.Solve(v.asDense(), trans, bm)
 }
diff --git a/mat/lu.go b/mat/lu.go
index 4f9a462c..5bef1e36 100644
--- a/mat/lu.go
+++ b/mat/lu.go
@@ -333,41 +333,46 @@ func (lu *LU) Solve(m *Dense, trans bool, b Matrix) error {
 //
 // If A is singular or near-singular a Condition error is returned. Please see
 // the documentation for Condition for more information.
-func (lu *LU) SolveVec(v *VecDense, trans bool, b *VecDense) error {
+func (lu *LU) SolveVec(v *VecDense, trans bool, b Vector) error {
 	_, n := lu.lu.Dims()
-	bn := b.Len()
-	if bn != n {
+	if br, bc := b.Dims(); br != n || bc != 1 {
 		panic(ErrShape)
 	}
-	if v != b {
-		v.checkOverlap(b.mat)
-	}
-	// TODO(btracey): Should test the condition number instead of testing that
-	// the determinant is exactly zero.
-	if lu.Det() == 0 {
-		return Condition(math.Inf(1))
-	}
+	switch rv := b.(type) {
+	default:
+		v.reuseAs(n)
+		return lu.Solve(v.asDense(), trans, b)
+	case RawVectorer:
+		if v != b {
+			v.checkOverlap(rv.RawVector())
+		}
+		// TODO(btracey): Should test the condition number instead of testing that
+		// the determinant is exactly zero.
+		if lu.Det() == 0 {
+			return Condition(math.Inf(1))
+		}
 
-	v.reuseAs(n)
-	var restore func()
-	if v == b {
-		v, restore = v.isolatedWorkspace(b)
-		defer restore()
+		v.reuseAs(n)
+		var restore func()
+		if v == b {
+			v, restore = v.isolatedWorkspace(b)
+			defer restore()
+		}
+		v.CopyVec(b)
+		vMat := blas64.General{
+			Rows:   n,
+			Cols:   1,
+			Stride: v.mat.Inc,
+			Data:   v.mat.Data,
+		}
+		t := blas.NoTrans
+		if trans {
+			t = blas.Trans
+		}
+		lapack64.Getrs(t, lu.lu.mat, vMat, lu.pivot)
+		if lu.cond > ConditionTolerance {
+			return Condition(lu.cond)
+		}
+		return nil
 	}
-	v.CopyVec(b)
-	vMat := blas64.General{
-		Rows:   n,
-		Cols:   1,
-		Stride: v.mat.Inc,
-		Data:   v.mat.Data,
-	}
-	t := blas.NoTrans
-	if trans {
-		t = blas.Trans
-	}
-	lapack64.Getrs(t, lu.lu.mat, vMat, lu.pivot)
-	if lu.cond > ConditionTolerance {
-		return Condition(lu.cond)
-	}
-	return nil
 }
diff --git a/mat/qr.go b/mat/qr.go
index 1d65ec9c..9ec0a28c 100644
--- a/mat/qr.go
+++ b/mat/qr.go
@@ -203,19 +203,31 @@ func (qr *QR) Solve(m *Dense, trans bool, b Matrix) error {
 	return nil
 }
 
-// SolveVec finds a minimum-norm solution to a system of linear equations.
+// SolveVec finds a minimum-norm solution to a system of linear equations,
+//  Ax = b.
 // Please see QR.Solve for the full documentation.
-func (qr *QR) SolveVec(v *VecDense, trans bool, b *VecDense) error {
-	if v != b {
-		v.checkOverlap(b.mat)
-	}
+func (qr *QR) SolveVec(v *VecDense, trans bool, b Vector) error {
 	r, c := qr.qr.Dims()
+	if _, bc := b.Dims(); bc != 1 {
+		panic(ErrShape)
+	}
+
 	// The Solve implementation is non-trivial, so rather than duplicate the code,
 	// instead recast the VecDenses as Dense and call the matrix code.
+	bm := Matrix(b)
+	if rv, ok := b.(RawVectorer); ok {
+		bmat := rv.RawVector()
+		if v != b {
+			v.checkOverlap(bmat)
+		}
+		b := VecDense{mat: bmat, n: b.Len()}
+		bm = b.asDense()
+	}
 	if trans {
 		v.reuseAs(r)
 	} else {
 		v.reuseAs(c)
 	}
-	return qr.Solve(v.asDense(), trans, b.asDense())
+	return qr.Solve(v.asDense(), trans, bm)
+
 }
diff --git a/mat/solve.go b/mat/solve.go
index e88812bd..c1e5b7eb 100644
--- a/mat/solve.go
+++ b/mat/solve.go
@@ -104,24 +104,37 @@ func (m *Dense) Solve(a, b Matrix) error {
 }
 
 // SolveVec finds a minimum-norm solution to a system of linear equations defined
-// by the matrix a and the right-hand side vector b. If A is singular or
+// by the matrix a and the right-hand side column vector b. If A is singular or
 // near-singular, a Condition error is returned. Please see the documentation for
 // Dense.Solve for more information.
-func (v *VecDense) SolveVec(a Matrix, b *VecDense) error {
-	if v != b {
-		v.checkOverlap(b.mat)
+func (v *VecDense) SolveVec(a Matrix, b Vector) error {
+	if _, bc := b.Dims(); bc != 1 {
+		panic(ErrShape)
 	}
 	_, c := a.Dims()
+
 	// The Solve implementation is non-trivial, so rather than duplicate the code,
 	// instead recast the VecDenses as Dense and call the matrix code.
+
+	if rv, ok := b.(RawVectorer); ok {
+		bmat := rv.RawVector()
+		if v != b {
+			v.checkOverlap(bmat)
+		}
+		v.reuseAs(c)
+		m := v.asDense()
+		// We conditionally create bm as m when b and v are identical
+		// to prevent the overlap detection code from identifying m
+		// and bm as overlapping but not identical.
+		bm := m
+		if v != b {
+			b := VecDense{mat: bmat, n: b.Len()}
+			bm = b.asDense()
+		}
+		return m.Solve(a, bm)
+	}
+
 	v.reuseAs(c)
 	m := v.asDense()
-	// We conditionally create bm as m when b and v are identical
-	// to prevent the overlap detection code from identifying m
-	// and bm as overlapping but not identical.
-	bm := m
-	if v != b {
-		bm = b.asDense()
-	}
-	return m.Solve(a, bm)
+	return m.Solve(a, b)
 }
diff --git a/mat/solve_test.go b/mat/solve_test.go
index d6bd6164..7f4c7362 100644
--- a/mat/solve_test.go
+++ b/mat/solve_test.go
@@ -285,13 +285,13 @@ func TestSolveVec(t *testing.T) {
 	// Use testTwoInput
 	method := func(receiver, a, b Matrix) {
 		type SolveVecer interface {
-			SolveVec(a Matrix, b *VecDense) error
+			SolveVec(a Matrix, b Vector) error
 		}
 		rd := receiver.(SolveVecer)
-		rd.SolveVec(a, b.(*VecDense))
+		rd.SolveVec(a, b.(Vector))
 	}
 	denseComparison := func(receiver, a, b *Dense) {
 		receiver.Solve(a, b)
 	}
-	testTwoInput(t, "SolveVec", &VecDense{}, method, denseComparison, legalTypesMatrixVecDense, legalSizeSolve, 1e-12)
+	testTwoInput(t, "SolveVec", &VecDense{}, method, denseComparison, legalTypesMatrixVector, legalSizeSolve, 1e-12)
 }