diff --git a/ldm/invoke/args.py b/ldm/invoke/args.py
index 3904d2f573..4707565424 100644
--- a/ldm/invoke/args.py
+++ b/ldm/invoke/args.py
@@ -196,6 +196,7 @@ class Args(object):
             elif os.path.exists(legacyinit):
                 print(f'>> WARNING: Old initialization file found at {legacyinit}. This location is deprecated. Please move it to {Globals.root}/invokeai.init.')
                 sysargs.insert(0,f'@{legacyinit}')
+            Globals.log_tokenization = self._arg_parser.parse_args(sysargs).log_tokenization
 
             self._arg_switches = self._arg_parser.parse_args(sysargs)
             return self._arg_switches
@@ -599,6 +600,12 @@ class Args(object):
             help=f'Set the default sampler. Supported samplers: {", ".join(SAMPLER_CHOICES)}',
             default='k_lms',
         )
+        render_group.add_argument(
+            '--log_tokenization',
+            '-t',
+            action='store_true',
+            help='shows how the prompt is split into tokens'
+        )
         render_group.add_argument(
             '-f',
             '--strength',
@@ -744,7 +751,7 @@ class Args(object):
                 invoke> !fetch 0000015.8929913.png
                 invoke> a fantastic alien landscape -W 576 -H 512 -s 60 -A plms -C 7.5
                 invoke> !fetch /path/to/images/*.png prompts.txt
- 
+
             !replay /path/to/prompts.txt
             Replays all the prompts contained in the file prompts.txt.
 
diff --git a/ldm/invoke/conditioning.py b/ldm/invoke/conditioning.py
index fec3c7e7b1..54ed10bc57 100644
--- a/ldm/invoke/conditioning.py
+++ b/ldm/invoke/conditioning.py
@@ -17,6 +17,7 @@ from ..models.diffusion import cross_attention_control
 from ..models.diffusion.shared_invokeai_diffusion import InvokeAIDiffuserComponent
 from ..modules.encoders.modules import WeightedFrozenCLIPEmbedder
 from ..modules.prompt_to_embeddings_converter import WeightedPromptFragmentsToEmbeddingsConverter
+from ldm.invoke.globals import Globals
 
 
 def get_uc_and_c_and_ec(prompt_string, model, log_tokens=False, skip_normalize_legacy_blend=False):
@@ -92,7 +93,7 @@ def _get_conditioning_for_prompt(parsed_prompt: Union[Blend, FlattenedPrompt], p
     Process prompt structure and tokens, and return (conditioning, unconditioning, extra_conditioning_info)
     """
 
-    if log_tokens:
+    if log_tokens or Globals.log_tokenization:
         print(f">> Parsed prompt to {parsed_prompt}")
         print(f">> Parsed negative prompt to {parsed_negative_prompt}")
 
@@ -235,7 +236,7 @@ def _get_embeddings_and_tokens_for_prompt(model, flattened_prompt: FlattenedProm
     fragments = [x.text for x in flattened_prompt.children]
     weights = [x.weight for x in flattened_prompt.children]
     embeddings, tokens = model.get_learned_conditioning([fragments], return_tokens=True, fragment_weights=[weights])
-    if log_tokens:
+    if log_tokens or Globals.log_tokenization:
         text = " ".join(fragments)
         log_tokenization(text, model, display_label=log_display_label)