diff --git a/tests/geometry/graph_test.py b/tests/geometry/graph_test.py
index 80a7fb8ee..0c71fc443 100644
--- a/tests/geometry/graph_test.py
+++ b/tests/geometry/graph_test.py
@@ -207,7 +207,7 @@ def laplacian(G: jnp.ndarray) -> jnp.ndarray:
   def test_graph_sinkhorn(self, rng: jax.random.PRNGKeyArray, jit: bool):
 
     def callback(geom: geometry.Geometry) -> sinkhorn.SinkhornOutput:
-      solver = sinkhorn.Sinkhorn(lse_mode=False, jit=False)
+      solver = sinkhorn.Sinkhorn(lse_mode=False)
       problem = linear_problem.LinearProblem(geom)
       return solver(problem)
 
diff --git a/tests/solvers/linear/sinkhorn_diff_test.py b/tests/solvers/linear/sinkhorn_diff_test.py
index 8512dcdae..6a0fdf6dc 100644
--- a/tests/solvers/linear/sinkhorn_diff_test.py
+++ b/tests/solvers/linear/sinkhorn_diff_test.py
@@ -157,8 +157,7 @@ def test_autograd_sinkhorn(
     def reg_ot(a: jnp.ndarray, b: jnp.ndarray) -> float:
       geom = pointcloud.PointCloud(x, y, epsilon=1e-1)
       prob = linear_problem.LinearProblem(geom, a=a, b=b)
-      # TODO: fails with `jit=True`, investigate
-      solver = sinkhorn.Sinkhorn(lse_mode=lse_mode, jit=False)
+      solver = sinkhorn.Sinkhorn(lse_mode=lse_mode)
       return solver(prob).reg_ot_cost
 
     reg_ot_and_grad = jax.jit(jax.grad(reg_ot))
@@ -275,8 +274,6 @@ def loss_fn(x: jnp.ndarray,
           lse_mode=lse_mode,
           min_iterations=min_iter,
           max_iterations=max_iter,
-          # TODO(cuturi): figure out why implicit diff breaks when `jit=True`
-          jit=False,
           implicit_diff=implicit_diff,
       )
       out = solver(prob)
diff --git a/tests/solvers/linear/sinkhorn_test.py b/tests/solvers/linear/sinkhorn_test.py
index bf0ff23d7..926f48442 100644
--- a/tests/solvers/linear/sinkhorn_test.py
+++ b/tests/solvers/linear/sinkhorn_test.py
@@ -465,8 +465,7 @@ def test_sinkhorn_online_memory_jit(self, batch_size: int):
     y = jax.random.uniform(rngs[1], (m, 2))
     geom = pointcloud.PointCloud(x, y, batch_size=batch_size, epsilon=1)
     problem = linear_problem.LinearProblem(geom)
-    solver = sinkhorn.Sinkhorn(jit=False)
-    solver = jax.jit(solver)
+    solver = jax.jit(sinkhorn.Sinkhorn())
 
     out = solver(problem)
     assert out.converged