diff --git a/src/diffusers/models/transformers/transformer_flux.py b/src/diffusers/models/transformers/transformer_flux.py
index 7ab371a1a1..d7a236462b 100644
--- a/src/diffusers/models/transformers/transformer_flux.py
+++ b/src/diffusers/models/transformers/transformer_flux.py
@@ -22,7 +22,8 @@ import torch.nn.functional as F
 
 from ...configuration_utils import ConfigMixin, register_to_config
 from ...loaders import FluxTransformer2DLoadersMixin, FromOriginalModelMixin, PeftAdapterMixin
-from ...utils import USE_PEFT_BACKEND, logging, scale_lora_layers, unscale_lora_layers
+from ...utils import USE_PEFT_BACKEND, is_kernels_available, logging, scale_lora_layers, unscale_lora_layers
+from ...utils.constants import DIFFUSERS_ENABLE_HUB_KERNELS
 from ...utils.torch_utils import maybe_allow_in_graph
 from ..attention import AttentionMixin, AttentionModuleMixin, FeedForward
 from ..attention_dispatch import dispatch_attention_fn
@@ -40,6 +41,12 @@ from ..normalization import AdaLayerNormContinuous, AdaLayerNormZero, AdaLayerNo
 
 logger = logging.get_logger(__name__)  # pylint: disable=invalid-name
 
+if is_kernels_available() and DIFFUSERS_ENABLE_HUB_KERNELS:
+    from kernels import get_kernel
+
+    activation = get_kernel("kernels-community/activation", revision="add_more_act")
+    gelu_tanh_kernel = activation.gelu_tanh
+
 
 def _get_projections(attn: "FluxAttention", hidden_states, encoder_hidden_states=None):
     query = attn.to_q(hidden_states)
@@ -350,7 +357,11 @@ class FluxSingleTransformerBlock(nn.Module):
 
         self.norm = AdaLayerNormZeroSingle(dim)
         self.proj_mlp = nn.Linear(dim, self.mlp_hidden_dim)
-        self.act_mlp = nn.GELU(approximate="tanh")
+        if not DIFFUSERS_ENABLE_HUB_KERNELS:
+            self.act_mlp = nn.GELU(approximate="tanh")
+        else:
+            self.act_mlp = gelu_tanh_kernel
+
         self.proj_out = nn.Linear(dim + self.mlp_hidden_dim, dim)
 
         self.attn = FluxAttention(