diff --git a/denoiser.hpp b/denoiser.hpp
index 3b6be7552..96366ceef 100644
--- a/denoiser.hpp
+++ b/denoiser.hpp
@@ -671,6 +671,7 @@ static void sample_k_diffusion(sample_method_t method,
                                ggml_context* work_ctx,
                                ggml_tensor* x,
                                std::vector<float> sigmas,
+                               int initial_step,
                                std::shared_ptr<RNG> rng,
                                float eta) {
     size_t steps = sigmas.size() - 1;
@@ -1248,12 +1249,13 @@ static void sample_k_diffusion(sample_method_t method,
                 // - pred_sample_direction -> "direction pointing to
                 //   x_t"
                 // - pred_prev_sample -> "x_t-1"
-                int timestep =
-                    roundf(TIMESTEPS -
-                           i * ((float)TIMESTEPS / steps)) -
-                    1;
+                int timestep = TIMESTEPS - 1 -
+                               (int)roundf((initial_step + i) *
+                                   (TIMESTEPS / float(initial_step + steps)));
                 // 1. get previous step value (=t-1)
-                int prev_timestep = timestep - TIMESTEPS / steps;
+                int prev_timestep = TIMESTEPS - 1 -
+                               (int)roundf((initial_step + i + 1) *
+                                   (TIMESTEPS / float(initial_step + steps)));
                 // The sigma here is chosen to cause the
                 // CompVisDenoiser to produce t = timestep
                 float sigma = compvis_sigmas[timestep];
@@ -1425,9 +1427,14 @@ static void sample_k_diffusion(sample_method_t method,
                 // Analytic form for TCD timesteps
                 int timestep = TIMESTEPS - 1 -
                                (TIMESTEPS / original_steps) *
-                                   (int)floor(i * ((float)original_steps / steps));
+                                   (int)floor((initial_step + i) *
+                                       ((float)original_steps / (initial_step + steps)));
                 // 1. get previous step value
-                int prev_timestep = i >= steps - 1 ? 0 : TIMESTEPS - 1 - (TIMESTEPS / original_steps) * (int)floor((i + 1) * ((float)original_steps / steps));
+                int prev_timestep = i >= steps - 1 ? 0 :
+                               TIMESTEPS - 1 -
+                               (TIMESTEPS / original_steps) *
+                                   (int)floor((initial_step + i + 1) *
+                                       ((float)original_steps / (initial_step + steps)));
                 // Here timestep_s is tau_n' in Algorithm 4. The _s
                 // notation appears to be that from C. Lu,
                 // "DPM-Solver: A Fast ODE Solver for Diffusion
diff --git a/stable-diffusion.cpp b/stable-diffusion.cpp
index 73065610d..f84d6c968 100644
--- a/stable-diffusion.cpp
+++ b/stable-diffusion.cpp
@@ -1480,6 +1480,7 @@ class StableDiffusionGGML {
                         int shifted_timestep,
                         sample_method_t method,
                         const std::vector<float>& sigmas,
+                        int initial_step,
                         int start_merge_step,
                         SDCondition id_cond,
                         std::vector<ggml_tensor*> ref_latents         = {},
@@ -1837,7 +1838,7 @@ class StableDiffusionGGML {
             return denoised;
         };
 
-        sample_k_diffusion(method, denoise, work_ctx, x, sigmas, sampler_rng, eta);
+        sample_k_diffusion(method, denoise, work_ctx, x, sigmas, initial_step, sampler_rng, eta);
 
         if (easycache_enabled) {
             size_t total_steps = sigmas.size() > 0 ? sigmas.size() - 1 : 0;
@@ -2762,6 +2763,7 @@ sd_image_t* generate_image_internal(sd_ctx_t* sd_ctx,
                                     int height,
                                     enum sample_method_t sample_method,
                                     const std::vector<float>& sigmas,
+                                    int initial_step,
                                     int64_t seed,
                                     int batch_count,
                                     sd_image_t control_image,
@@ -3056,6 +3058,7 @@ sd_image_t* generate_image_internal(sd_ctx_t* sd_ctx,
                                                      shifted_timestep,
                                                      sample_method,
                                                      sigmas,
+                                                     initial_step,
                                                      start_merge_step,
                                                      id_cond,
                                                      ref_latents,
@@ -3173,6 +3176,7 @@ sd_image_t* generate_image(sd_ctx_t* sd_ctx, const sd_img_gen_params_t* sd_img_g
                                                                  sd_ctx->sd->get_image_seq_len(height, width),
                                                                  sd_img_gen_params->sample_params.scheduler,
                                                                  sd_ctx->sd->version);
+    int initial_step = 0;
 
     ggml_tensor* init_latent   = nullptr;
     ggml_tensor* concat_latent = nullptr;
@@ -3185,7 +3189,8 @@ sd_image_t* generate_image(sd_ctx_t* sd_ctx, const sd_img_gen_params_t* sd_img_g
             t_enc--;
         LOG_INFO("target t_enc is %zu steps", t_enc);
         std::vector<float> sigma_sched;
-        sigma_sched.assign(sigmas.begin() + sample_steps - t_enc - 1, sigmas.end());
+        initial_step = sample_steps - t_enc - 1;
+        sigma_sched.assign(sigmas.begin() + initial_step, sigmas.end());
         sigmas = sigma_sched;
 
         ggml_tensor* init_img = ggml_new_tensor_4d(work_ctx, GGML_TYPE_F32, width, height, 3, 1);
@@ -3373,6 +3378,7 @@ sd_image_t* generate_image(sd_ctx_t* sd_ctx, const sd_img_gen_params_t* sd_img_g
                                                         height,
                                                         sample_method,
                                                         sigmas,
+                                                        initial_step,
                                                         seed,
                                                         sd_img_gen_params->batch_count,
                                                         sd_img_gen_params->control_image,
@@ -3709,6 +3715,7 @@ SD_API sd_image_t* generate_video(sd_ctx_t* sd_ctx, const sd_vid_gen_params_t* s
                                  sd_vid_gen_params->high_noise_sample_params.shifted_timestep,
                                  high_noise_sample_method,
                                  high_noise_sigmas,
+                                 0,
                                  -1,
                                  {},
                                  {},
@@ -3746,6 +3753,7 @@ SD_API sd_image_t* generate_video(sd_ctx_t* sd_ctx, const sd_vid_gen_params_t* s
                                           sd_vid_gen_params->sample_params.shifted_timestep,
                                           sample_method,
                                           sigmas,
+                                          0,
                                           -1,
                                           {},
                                           {},