diff --git a/benchmarks/math_benchmark.py b/benchmarks/math_benchmark.py
index 2dc95263f..4a0a0b7a6 100644
--- a/benchmarks/math_benchmark.py
+++ b/benchmarks/math_benchmark.py
@@ -72,6 +72,61 @@ def jax_unary(state, **kwargs):
       input0.size * state.iterations, Counter.kIsRate
   )
 
+@math_benchmark(
+    [
+        {
+            'name': f'{op.__name__}_{mkn[0]}x{mkn[1]}x{mkn[2]}_{dtype}',
+            'mkn': mkn,
+            'dtype': dtype,
+            'op': op,
+        }
+        for op in [
+            jnp.dot,
+        ]
+        for mkn in [[2**i, 2**i, 2**i] for i in range(4, 11, 1)] +
+        [
+            [1, 2, 256],
+            [1, 8, 256],
+            [1, 18, 300],
+            [1, 37, 256],
+            [1, 91, 256],
+            [1, 111, 256],
+            [1, 192, 192],
+            [1, 226, 256],
+            [1, 256, 192],
+            [1, 256, 256],
+            [1, 512, 512],
+            [1, 300, 18],
+            [21, 24, 1],
+            [21, 120, 1],
+            [10, 10, 10],
+            [100, 100, 100],
+            [18, 1, 300],
+            [18, 300, 1],
+            [300, 1, 18],
+            [300, 18, 1],
+        ]
+        for dtype in ['float32']
+    ]
+)
+def jax_binary_op(state, **kwargs):
+  mkn = kwargs['mkn']
+  m = mkn[0]
+  k = mkn[1]
+  n = mkn[2]
+  dtype = kwargs['dtype']
+  op = kwargs['op']
+  a = np.random.random([m, k]).astype(dtype)
+  b = np.random.random([k, n]).astype(dtype)
+  f = op
+  f_jitted = jax.jit(f)
+  f_jitted(a, b).block_until_ready()
+  while state:
+    f_jitted(a, b).block_until_ready()
+  state.counters['items_per_second'] = Counter(
+      state.iterations, Counter.kIsRate
+  )
+
 
 if __name__ == '__main__':
   benchmark.main()