diff --git a/modules/sd_samplers_cfg_denoiser.py b/modules/sd_samplers_cfg_denoiser.py
index a73d3b036..93581c9ac 100644
--- a/modules/sd_samplers_cfg_denoiser.py
+++ b/modules/sd_samplers_cfg_denoiser.py
@@ -152,7 +152,7 @@ class CFGDenoiser(torch.nn.Module):
         if state.interrupted or state.skipped:
             raise sd_samplers_common.InterruptedException
 
-        if sd_samplers_common.apply_refiner(self):
+        if sd_samplers_common.apply_refiner(self, sigma):
             cond = self.sampler.sampler_extra_args['cond']
             uncond = self.sampler.sampler_extra_args['uncond']
 
diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py
index 6bd38e12a..045b9e2fe 100644
--- a/modules/sd_samplers_common.py
+++ b/modules/sd_samplers_common.py
@@ -155,8 +155,17 @@ def replace_torchsde_browinan():
 replace_torchsde_browinan()
 
 
-def apply_refiner(cfg_denoiser):
-    completed_ratio = cfg_denoiser.step / cfg_denoiser.total_steps
+def apply_refiner(cfg_denoiser, sigma):
+    if opts.refiner_switch_by_sample_steps:
+        completed_ratio = cfg_denoiser.step / cfg_denoiser.total_steps
+    else:
+        # torch.max(sigma) only to handle rare case where we might have different sigmas in the same batch
+        try:
+            timestep = torch.argmin(torch.abs(cfg_denoiser.inner_model.sigmas - torch.max(sigma)))
+        except AttributeError: # for samplers that dont use sigmas (DDIM) sigma is actually the timestep
+            timestep = torch.max(sigma).to(dtype=int)
+        completed_ratio = (999 - timestep) / 1000
+
     refiner_switch_at = cfg_denoiser.p.refiner_switch_at
     refiner_checkpoint_info = cfg_denoiser.p.refiner_checkpoint_info
 
diff --git a/modules/shared_options.py b/modules/shared_options.py
index aa26588df..073454c6a 100644
--- a/modules/shared_options.py
+++ b/modules/shared_options.py
@@ -227,7 +227,8 @@ options_templates.update(options_section(('compatibility', "Compatibility", "sd"
     "dont_fix_second_order_samplers_schedule": OptionInfo(False, "Do not fix prompt schedule for second order samplers."),
     "hires_fix_use_firstpass_conds": OptionInfo(False, "For hires fix, calculate conds of second pass using extra networks of first pass."),
     "use_old_scheduling": OptionInfo(False, "Use old prompt editing timelines.", infotext="Old prompt editing timelines").info("For [red:green:N]; old: If N < 1, it's a fraction of steps (and hires fix uses range from 0 to 1), if N >= 1, it's an absolute number of steps; new: If N has a decimal point in it, it's a fraction of steps (and hires fix uses range from 1 to 2), othewrwise it's an absolute number of steps"),
-    "use_downcasted_alpha_bar": OptionInfo(False, "Downcast model alphas_cumprod to fp16 before sampling. For reproducing old seeds.", infotext="Downcast alphas_cumprod")
+    "use_downcasted_alpha_bar": OptionInfo(False, "Downcast model alphas_cumprod to fp16 before sampling. For reproducing old seeds.", infotext="Downcast alphas_cumprod"),
+    "refiner_switch_by_sample_steps": OptionInfo(False, "Switch to refiner by sampling steps instead of model timesteps. Old behavior for refiner.", infotext="Refiner switch by sampling steps")
 }))
 
 options_templates.update(options_section(('interrogate', "Interrogate"), {