diff --git a/tests/test_pipelines_flax.py b/tests/test_pipelines_flax.py
index a461930f3a83..aab2eb9a07fb 100644
--- a/tests/test_pipelines_flax.py
+++ b/tests/test_pipelines_flax.py
@@ -28,7 +28,6 @@
     import jax.numpy as jnp
     from flax.jax_utils import replicate
     from flax.training.common_utils import shard
-    from jax import pmap
 
     from diffusers import FlaxDDIMScheduler, FlaxDiffusionPipeline, FlaxStableDiffusionPipeline
 
@@ -70,14 +69,12 @@ def test_dummy_all_tpus(self):
         prompt = num_samples * [prompt]
         prompt_ids = pipeline.prepare_inputs(prompt)
 
-        p_sample = pmap(pipeline.__call__, static_broadcasted_argnums=(3,))
-
         # shard inputs and rng
         params = replicate(params)
         prng_seed = jax.random.split(prng_seed, num_samples)
         prompt_ids = shard(prompt_ids)
 
-        images = p_sample(prompt_ids, params, prng_seed, num_inference_steps).images
+        images = pipeline(prompt_ids, params, prng_seed, num_inference_steps, jit=True).images
 
         assert images.shape == (num_samples, 1, 64, 64, 3)
         if jax.device_count() == 8:
@@ -105,14 +102,12 @@ def test_stable_diffusion_v1_4(self):
         prompt = num_samples * [prompt]
         prompt_ids = pipeline.prepare_inputs(prompt)
 
-        p_sample = pmap(pipeline.__call__, static_broadcasted_argnums=(3,))
-
         # shard inputs and rng
         params = replicate(params)
         prng_seed = jax.random.split(prng_seed, num_samples)
         prompt_ids = shard(prompt_ids)
 
-        images = p_sample(prompt_ids, params, prng_seed, num_inference_steps).images
+        images = pipeline(prompt_ids, params, prng_seed, num_inference_steps, jit=True).images
 
         assert images.shape == (num_samples, 1, 512, 512, 3)
         if jax.device_count() == 8:
@@ -136,14 +131,12 @@ def test_stable_diffusion_v1_4_bfloat_16(self):
         prompt = num_samples * [prompt]
         prompt_ids = pipeline.prepare_inputs(prompt)
 
-        p_sample = pmap(pipeline.__call__, static_broadcasted_argnums=(3,))
-
         # shard inputs and rng
         params = replicate(params)
         prng_seed = jax.random.split(prng_seed, num_samples)
         prompt_ids = shard(prompt_ids)
 
-        images = p_sample(prompt_ids, params, prng_seed, num_inference_steps).images
+        images = pipeline(prompt_ids, params, prng_seed, num_inference_steps, jit=True).images
 
         assert images.shape == (num_samples, 1, 512, 512, 3)
         if jax.device_count() == 8:
@@ -211,14 +204,12 @@ def test_stable_diffusion_v1_4_bfloat_16_ddim(self):
         prompt = num_samples * [prompt]
         prompt_ids = pipeline.prepare_inputs(prompt)
 
-        p_sample = pmap(pipeline.__call__, static_broadcasted_argnums=(3,))
-
         # shard inputs and rng
         params = replicate(params)
         prng_seed = jax.random.split(prng_seed, num_samples)
         prompt_ids = shard(prompt_ids)
 
-        images = p_sample(prompt_ids, params, prng_seed, num_inference_steps).images
+        images = pipeline(prompt_ids, params, prng_seed, num_inference_steps, jit=True).images
 
         assert images.shape == (num_samples, 1, 512, 512, 3)
         if jax.device_count() == 8: