diff --git a/gensim/models/lsimodel.py b/gensim/models/lsimodel.py
index cce19b0b6b..b6fb4bf125 100644
--- a/gensim/models/lsimodel.py
+++ b/gensim/models/lsimodel.py
@@ -66,7 +66,6 @@
 import numpy as np
 import scipy.linalg
 import scipy.sparse
-from scipy.sparse import sparsetools
 
 from gensim import interfaces, matutils, utils
 from gensim.models import basemodel
@@ -960,10 +959,8 @@ def stochastic_svd(
         m, n = corpus.shape
         assert num_terms == m, f"mismatch in number of features: {m} in sparse matrix vs. {num_terms} parameter"
         o = random_state.normal(0.0, 1.0, (n, samples)).astype(y.dtype)  # draw a random gaussian matrix
-        sparsetools.csc_matvecs(
-            m, n, samples, corpus.indptr, corpus.indices,
-            corpus.data, o.ravel(), y.ravel(),
-        )  # y = corpus * o
+        y = corpus.dot(o) # y = corpus * o
+
         del o
 
         # unlike np, scipy.sparse `astype()` copies everything, even if there is no change to dtype!
@@ -994,10 +991,7 @@ def stochastic_svd(
             num_docs += n
             logger.debug("multiplying chunk * gauss")
             o = random_state.normal(0.0, 1.0, (n, samples), ).astype(dtype)  # draw a random gaussian matrix
-            sparsetools.csc_matvecs(
-                m, n, samples, chunk.indptr, chunk.indices,  # y = y + chunk * o
-                chunk.data, o.ravel(), y.ravel(),
-            )
+            y = y + chunk * o
             del chunk, o
         y = [y]
         q, _ = matutils.qr_destroy(y)  # orthonormalize the range