diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/DotBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/DotBenchmark.kt
index 4a5cd4aa2..16fd544a8 100644
--- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/DotBenchmark.kt
+++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/DotBenchmark.kt
@@ -15,10 +15,8 @@ import space.kscience.kmath.linear.invoke
 import space.kscience.kmath.linear.linearSpace
 import space.kscience.kmath.multik.multikAlgebra
 import space.kscience.kmath.operations.DoubleField
-import space.kscience.kmath.operations.invoke
 import space.kscience.kmath.structures.Buffer
 import space.kscience.kmath.tensorflow.produceWithTF
-import space.kscience.kmath.tensors.core.DoubleTensorAlgebra
 import space.kscience.kmath.tensors.core.tensorAlgebra
 import kotlin.random.Random
 
@@ -36,9 +34,6 @@ internal class DotBenchmark {
             random.nextDouble()
         }
 
-        val tensor1 = DoubleTensorAlgebra.randomNormal(shape = intArrayOf(dim, dim), 12224)
-        val tensor2 = DoubleTensorAlgebra.randomNormal(shape = intArrayOf(dim, dim), 12225)
-
         val cmMatrix1 = CMLinearSpace { matrix1.toCM() }
         val cmMatrix2 = CMLinearSpace { matrix2.toCM() }
 
@@ -48,10 +43,10 @@ internal class DotBenchmark {
 
 
     @Benchmark
-    fun tfDot(blackhole: Blackhole){
+    fun tfDot(blackhole: Blackhole) {
         blackhole.consume(
             DoubleField.produceWithTF {
-                tensor1 dot tensor2
+                matrix1 dot matrix1
             }
         )
     }
@@ -95,9 +90,4 @@ internal class DotBenchmark {
     fun doubleDot(blackhole: Blackhole) = with(DoubleField.linearSpace) {
         blackhole.consume(matrix1 dot matrix2)
     }
-
-    @Benchmark
-    fun doubleTensorDot(blackhole: Blackhole) = DoubleTensorAlgebra.invoke {
-        blackhole.consume(tensor1 dot tensor2)
-    }
 }