goyaladitya05 · goyaladitya05 · Mar 18, 2026 · Mar 18, 2026
diff --git a/samples/cpp/video_generation/CMakeLists.txt b/samples/cpp/video_generation/CMakeLists.txt
@@ -74,29 +74,3 @@ install(TARGETS taylorseer_text2video
         RUNTIME DESTINATION samples_bin/
         COMPONENT samples_bin
         EXCLUDE_FROM_ALL)
-
-# create LoRA sample executable
-add_executable(lora_text2video lora_text2video.cpp imwrite_video.cpp)
-
-target_include_directories(lora_text2video PRIVATE ${CMAKE_BINARY_DIR} "${CMAKE_CURRENT_SOURCE_DIR}/../image_generation/" "${CMAKE_CURRENT_SOURCE_DIR}/../../../src/cpp/src/")
-ov_genai_link_opencv(lora_text2video core imgproc videoio imgcodecs)
-target_link_libraries(lora_text2video PRIVATE openvino::genai indicators::indicators)
-
-if(UNIX AND NOT APPLE)
-    set_target_properties(lora_text2video PROPERTIES
-        INSTALL_RPATH "$ORIGIN/../lib"
-    )
-elseif(APPLE)
-    set_target_properties(lora_text2video PROPERTIES
-        INSTALL_RPATH "@loader_path/../lib"
-    )
-endif()
-
-set_target_properties(lora_text2video PROPERTIES
-    # Ensure out of box LC_RPATH on macOS with SIP
-    INSTALL_RPATH_USE_LINK_PATH ON)
-
-install(TARGETS lora_text2video
-        RUNTIME DESTINATION samples_bin/
-        COMPONENT samples_bin
-        EXCLUDE_FROM_ALL)
diff --git a/samples/cpp/video_generation/README.md b/samples/cpp/video_generation/README.md
@@ -24,18 +24,18 @@ pip install --upgrade-strategy eager -r ../../export-requirements.txt
 Then, run the export with Optimum CLI:
 
 ```sh
-optimum-cli export openvino --model Lightricks/LTX-Video --task text-to-video --weight-format fp32 ltx_video_ov/FP32
+optimum-cli export openvino --model Lightricks/LTX-Video --task text-to-video --weight-format int8 ltx_video_ov/INT8
 ```
 
-> **Note:** `--weight-format fp32` is required for LoRA adapter support. For basic video generation without LoRA, `--weight-format int8` produces a smaller model.
-
-Alternatively, do it in Python code:
+Alternatively, do it in Python code. If NNCF is installed, the model will be compressed to INT8 automatically.
 
 ```python
 from optimum.intel.openvino import OVLTXPipeline
 
-pipeline = OVLTXPipeline.from_pretrained("Lightricks/LTX-Video", export=True, compile=False)
-pipeline.save_pretrained("ltx_video_ov/FP32")
+output_dir = "ltx_video_ov/INT8"
+
+pipeline = OVLTXPipeline.from_pretrained("Lightricks/LTX-Video", export=True, compile=False, load_in_8bit=True)
+pipeline.save_pretrained(output_dir)
 ```
 
 ## Sample Descriptions
@@ -63,34 +63,10 @@ GPUs usually provide better performance compared to CPUs. Modify the source code
 
   Example:
   ```bash
-  ./text2video ltx_video_ov/FP32 "A woman with long brown hair and light skin smiles at another woman with long blonde hair"
-  ```
-
-### LoRA Text to Video Sample (`lora_text2video.cpp`)
-
-- **Description:**
-  Video generation with LoRA adapters using a text-to-video model. This sample demonstrates how to generate videos from text prompts while applying multiple LoRA adapters.
-
-  Recommended models: Lightricks/LTX-Video
-
-  To download the LoRA adapter used in the example below:
-  ```sh
-  huggingface-cli download svjack/ltx_video_pixel_early_lora ltx_pixel_pytorch_lora_weights.safetensors
-  ```
-
-- **Main Feature:** Apply LoRA adapters to a text-to-video pipeline for customized generation.
-
-- **Run Command:**
-  ```bash
-  ./lora_text2video model_dir prompt [lora_adapter_path alpha] ...
-  ```
-
-  Example:
-  ```bash
-  ./lora_text2video ltx_video_ov/FP32 "In the style of Pixel, the video shifts to a majestic castle under a starry sky." ltx_pixel_pytorch_lora_weights.safetensors 3.0
+  ./text2video ltx_video_ov/INT8 "A woman with long brown hair and light skin smiles at another woman with long blonde hair"
   ```
 
-The LoRA text-to-video sample will generate two video files, `lora_video.avi` and `baseline_video.avi`, in the current directory.
+The sample will generate a video file `genai_video.avi` in the current directory.
 
 Users can modify the source code to experiment with different generation parameters:
 - Change width or height of generated video

diff --git a/samples/cpp/video_generation/lora_text2video.cpp b/samples/cpp/video_generation/lora_text2video.cpp
diff --git a/samples/python/video_generation/README.md b/samples/python/video_generation/README.md
@@ -24,18 +24,18 @@ pip install --upgrade-strategy eager -r ../../export-requirements.txt
 Then, run the export with Optimum CLI:
 
 ```sh
-optimum-cli export openvino --model Lightricks/LTX-Video --task text-to-video --weight-format fp32 ltx_video_ov/FP32
+optimum-cli export openvino --model Lightricks/LTX-Video --task text-to-video --weight-format int8 ltx_video_ov/INT8
 ```
 
-> **Note:** For basic video generation without LoRA, `--weight-format int8` produces a smaller model.
-
-Alternatively, do it in Python code:
+Alternatively, do it in Python code. If NNCF is installed, the model will be compressed to INT8 automatically.
 
 ```python
 from optimum.intel.openvino import OVLTXPipeline
 
-pipeline = OVLTXPipeline.from_pretrained("Lightricks/LTX-Video", export=True, compile=False)
-pipeline.save_pretrained("ltx_video_ov/FP32")
+output_dir = "ltx_video_ov/INT8"
+
+pipeline = OVLTXPipeline.from_pretrained("Lightricks/LTX-Video", export=True, compile=False, load_in_8bit=True)
+pipeline.save_pretrained(output_dir)
 ```
 
 ## Sample Descriptions
@@ -68,34 +68,10 @@ pip install --upgrade-strategy eager -r ../../deployment-requirements.txt
 
   Example:
   ```bash
-  python text2video.py ./ltx_video_ov/FP32 "A woman with long brown hair and light skin smiles at another woman with long blonde hair"
-  ```
-
-### LoRA Text to Video Sample (`lora_text2video.py`)
-
-- **Description:**
-  Video generation with LoRA adapters using a text-to-video model. This sample demonstrates how to generate videos from text prompts while applying a LoRA adapter.
-
-  Recommended models: Lightricks/LTX-Video
-
-  To download the LoRA adapter used in the example below:
-  ```sh
-  huggingface-cli download svjack/ltx_video_pixel_early_lora ltx_pixel_pytorch_lora_weights.safetensors
-  ```
-
-- **Main Feature:** Apply a LoRA adapter to a text-to-video pipeline for customized generation.
-
-- **Run Command:**
-  ```bash
-  python lora_text2video.py model_dir prompt [lora_adapter_path alpha] ...
-  ```
-
-  Example:
-  ```bash
-  python lora_text2video.py ./ltx_video_ov/FP32 "In the style of Pixel, the video shifts to a majestic castle under a starry sky." ltx_pixel_pytorch_lora_weights.safetensors 3.0
+  python text2video.py ./ltx_video_ov/INT8 "A woman with long brown hair and light skin smiles at another woman with long blonde hair"
   ```
 
-The sample will generate two video files, `lora_video.avi` and `baseline_video.avi`, in the current directory.
+The sample will generate a video file `genai_video.avi` in the current directory.
 
 Users can modify the source code to experiment with different generation parameters:
 - Change width or height of generated video

diff --git a/samples/python/video_generation/lora_text2video.py b/samples/python/video_generation/lora_text2video.py
diff --git a/site/docs/guides/lora-adapters.mdx b/site/docs/guides/lora-adapters.mdx
@@ -13,7 +13,7 @@ LoRA adapters enable customization of model outputs for specific tasks, styles,
 For more details about LoRA, see [Low-Rank Adaptation (LoRA)](/docs/concepts/lora).
 :::
 
-OpenVINO GenAI provides built-in support for LoRA adapters in [text generation](/docs/use-cases/text-generation/), [image generation](/docs/use-cases/image-generation/), [image processing (VLM)](/docs/use-cases/image-processing), and [video generation](/docs/use-cases/video-generation/) pipelines.
+OpenVINO GenAI provides built-in support for LoRA adapters in [text generation](/docs/use-cases/text-generation/), [image generation](/docs/use-cases/image-generation/), and [image processing (VLM)](/docs/use-cases/image-processing) pipelines.
 This capability allows you to dynamically switch between or combine multiple adapters without recompiling the model.
 
 :::info

diff --git a/site/docs/use-cases/video-generation/_sections/_usage_options/index.mdx b/site/docs/use-cases/video-generation/_sections/_usage_options/index.mdx
@@ -66,12 +66,6 @@ You can adjust several parameters to control the video generation process, inclu
     </TabItemCpp>
 </LanguageTabs>
 
-### Working with LoRA Adapters
-
-For video generation models like LTX-Video, LoRA adapters can modify the generation process to produce videos with specific artistic styles, content types, or quality enhancements.
-
-Refer to the [LoRA Adapters](/docs/guides/lora-adapters) for more details on working with LoRA adapters.
-
 :::info Understanding Video Generation Parameters
 
 - `negative_prompt`: Negative prompt for video(s) generation.

diff --git a/src/cpp/include/openvino/genai/lora_adapter.hpp b/src/cpp/include/openvino/genai/lora_adapter.hpp
@@ -22,7 +22,6 @@ namespace genai {
 class OPENVINO_GENAI_EXPORTS AdapterController;
 struct AdapterControllerImpl;
 class AdapterImpl;
-struct AdapterConfig;
 
 // Immutable LoRA Adapter that carries the adaptation matrices and serves as unique adapter identifier
 class OPENVINO_GENAI_EXPORTS Adapter {
@@ -34,7 +33,6 @@ class OPENVINO_GENAI_EXPORTS Adapter {
 
     friend Adapter flux_adapter_normalization(const Adapter& adapter);
     friend Adapter diffusers_adapter_normalization(const Adapter& adapter);
-    friend std::string detect_lora_prefix(const AdapterConfig& adapters);
 
     Adapter(const std::shared_ptr<AdapterImpl>& pimpl);
 public:

diff --git a/src/cpp/include/openvino/genai/video_generation/generation_config.hpp b/src/cpp/include/openvino/genai/video_generation/generation_config.hpp
@@ -7,7 +7,7 @@
 #include <optional>
 
 #include "openvino/genai/image_generation/generation_config.hpp"
-#include "openvino/genai/lora_adapter.hpp"
+
 
 namespace ov::genai {
 /**
@@ -63,9 +63,6 @@ struct VideoGenerationConfig {
      * and predicts outputs using Taylor series approximation.
      */
     std::optional<TaylorSeerCacheConfig> taylorseer_config;
-
-    /// LoRA adapters applied during generation.
-    std::optional<AdapterConfig> adapters = std::nullopt;
 };
 
 /**

diff --git a/src/cpp/include/openvino/genai/video_generation/ltx_video_transformer_3d_model.hpp b/src/cpp/include/openvino/genai/video_generation/ltx_video_transformer_3d_model.hpp
@@ -11,7 +11,6 @@
 #include "openvino/runtime/infer_request.hpp"
 #include "openvino/runtime/properties.hpp"
 #include "openvino/runtime/tensor.hpp"
-#include "openvino/genai/lora_adapter.hpp"
 #include "openvino/genai/visibility.hpp"
 
 namespace ov::genai {
@@ -47,8 +46,6 @@ class OPENVINO_GENAI_EXPORTS LTXVideoTransformer3DModel {
 
     void set_hidden_states(const std::string& tensor_name, const ov::Tensor& encoder_hidden_states);
 
-    void set_adapters(const std::optional<AdapterConfig>& adapters);
-
     ov::Tensor infer(const ov::Tensor& latent, const ov::Tensor& timestep);
 
     LTXVideoTransformer3DModel& reshape(int64_t batch_size, int64_t num_frames, int64_t height, int64_t width, int64_t tokenizer_model_max_length);
@@ -61,8 +58,6 @@ class OPENVINO_GENAI_EXPORTS LTXVideoTransformer3DModel {
     std::shared_ptr<Inference> m_impl;
 
     Config m_config;
-    AdapterController m_adapter_controller;
-    std::string m_lora_prefix;
     ov::InferRequest m_request;
     std::shared_ptr<ov::Model> m_model;
     size_t m_expected_batch_size = 0;