diff --git a/python/sglang/multimodal_gen/.claude/skills/sglang-diffusion-benchmark-profile/SKILL.md b/python/sglang/multimodal_gen/.claude/skills/sglang-diffusion-benchmark-profile/SKILL.md
index d91f2c2a2..29b12dab0 100644
--- a/python/sglang/multimodal_gen/.claude/skills/sglang-diffusion-benchmark-profile/SKILL.md
+++ b/python/sglang/multimodal_gen/.claude/skills/sglang-diffusion-benchmark-profile/SKILL.md
@@ -27,7 +27,7 @@ Before running any benchmark, profiler, or kernel-validation command:
 
 ## Main Reference
 
-- [benchmark-and-profile.md](benchmark-and-profile.md) — canonical denoise benchmark, perf dump, and `torch.profiler` workflow; uses the checked-in nightly-aligned presets, including `LTX-2` two-stage
+- [benchmark-and-profile.md](benchmark-and-profile.md) — canonical denoise benchmark, perf dump, and `torch.profiler` workflow; uses the checked-in nightly-aligned presets, plus `LTX-2`, `LTX-2.3` one-stage, and `LTX-2.3` two-stage benchmark recipes
 - [existing-fast-paths.md](existing-fast-paths.md) — map bottlenecks to existing fused kernels, packed QKV paths, fused `QK norm + RoPE`, and distributed overlap patterns before proposing new code
 - [scripts/diffusion_skill_env.py](scripts/diffusion_skill_env.py) — preflight helper: repo root discovery via `sglang.__file__`, write-access probe, benchmark/profile output directories, idle GPU selection
 - [scripts/bench_diffusion_denoise.py](scripts/bench_diffusion_denoise.py) — end-to-end denoise benchmark preset runner via `sglang generate`; use `--list-models` to inspect preset order, then save perf dumps by label and compare them with `compare_perf.py`
diff --git a/python/sglang/multimodal_gen/.claude/skills/sglang-diffusion-benchmark-profile/benchmark-and-profile.md b/python/sglang/multimodal_gen/.claude/skills/sglang-diffusion-benchmark-profile/benchmark-and-profile.md
index be4aac215..4ea949fb7 100644
--- a/python/sglang/multimodal_gen/.claude/skills/sglang-diffusion-benchmark-profile/benchmark-and-profile.md
+++ b/python/sglang/multimodal_gen/.claude/skills/sglang-diffusion-benchmark-profile/benchmark-and-profile.md
@@ -100,6 +100,26 @@ PYTHONPATH=python python3 \
   --output-dir "${BENCH_DIR}"
 ```
 
+Run the `LTX-2.3` one-stage skill preset:
+
+```bash
+PYTHONPATH=python python3 \
+  python/sglang/multimodal_gen/.claude/skills/sglang-diffusion-benchmark-profile/scripts/bench_diffusion_denoise.py \
+  --model ltx23-one-stage \
+  --label baseline \
+  --output-dir "${BENCH_DIR}"
+```
+
+Run the `LTX-2.3` two-stage skill preset:
+
+```bash
+PYTHONPATH=python python3 \
+  python/sglang/multimodal_gen/.claude/skills/sglang-diffusion-benchmark-profile/scripts/bench_diffusion_denoise.py \
+  --model ltx23-two-stage \
+  --label baseline \
+  --output-dir "${BENCH_DIR}"
+```
+
 Run the full preset sweep:
 
 ```bash
@@ -123,6 +143,8 @@ Nightly-aligned presets come first; skill-only presets stay available after them
 | `wan-ti2v` | `Wan-AI/Wan2.2-TI2V-5B-Diffusers` | Yes: `wan22_ti2v_5b_720p` | Uses the nightly cat image and motion prompt |
 | `ltx2` | `Lightricks/LTX-2` | Yes: `ltx2_twostage_t2v` | Uses `LTX2TwoStagePipeline`; nightly-aligned prompt, negative prompt, 1536x1024, 121 frames, fps 24, seed 1234 |
 | `wan-i2v` | `Wan-AI/Wan2.2-I2V-A14B-Diffusers` | Yes: `wan22_i2v_a14b_720p` | Aligned to nightly CFG-parallel 4-GPU launch |
+| `ltx23-one-stage` | `Lightricks/LTX-2.3` | No | Skill-only extra preset for the native `LTX-2.3` one-stage baseline; 2 GPUs, 768x512, 121 frames, fps 24, 30 steps, guidance 3.0, seed 1234 |
+| `ltx23-two-stage` | `Lightricks/LTX-2.3` | No | Skill-only extra preset for the native `LTX-2.3` two-stage path; uses `LTX2TwoStagePipeline`, 2 GPUs, 1536x1024, 121 frames, fps 24, 30 steps, guidance 3.0, seed 1234 |
 | `hunyuanvideo` | `hunyuanvideo-community/HunyuanVideo` | No | Skill-only extra preset |
 | `mova-720p` | `OpenMOSS-Team/MOVA-720p` | No | Skill-only extra preset |
 | `helios` | `BestWishYsh/Helios-Base` | No | Skill-only extra preset |
@@ -151,6 +173,41 @@ After [PR #20707](https://github.com/sgl-project/sglang/pull/20707),
 `LTX2TwoStagePipeline` is a native path. The spatial upsampler and distilled
 LoRA are auto-resolved from the same model snapshot unless you override them.
 
+### Manual command example: LTX-2.3 One-Stage
+
+```bash
+sglang generate \
+  --model-path=Lightricks/LTX-2.3 \
+  --prompt="A beautiful sunset over the ocean" \
+  --negative-prompt="shaky, glitchy, low quality, worst quality, deformed, distorted, disfigured, motion smear, motion artifacts, fused fingers, bad anatomy, weird hand, ugly, transition, static." \
+  --width=768 --height=512 \
+  --num-frames=121 --fps=24 \
+  --num-inference-steps=30 --guidance-scale=3.0 \
+  --seed=1234 --num-gpus=2 \
+  --save-output --enable-torch-compile --warmup
+```
+
+Use this when you want the native `LTX2Pipeline` baseline for `LTX-2.3` at the
+validated one-stage resolution.
+
+### Manual command example: LTX-2.3 Two-Stage
+
+```bash
+sglang generate \
+  --model-path=Lightricks/LTX-2.3 \
+  --pipeline-class-name=LTX2TwoStagePipeline \
+  --prompt="A beautiful sunset over the ocean" \
+  --negative-prompt="shaky, glitchy, low quality, worst quality, deformed, distorted, disfigured, motion smear, motion artifacts, fused fingers, bad anatomy, weird hand, ugly, transition, static." \
+  --width=1536 --height=1024 \
+  --num-frames=121 --fps=24 \
+  --num-inference-steps=30 --guidance-scale=3.0 \
+  --seed=1234 --num-gpus=2 \
+  --save-output --enable-torch-compile --warmup
+```
+
+This matches the new `ltx23-two-stage` skill preset and is a good benchmark target for
+the recently merged `LTX-2.3` two-stage path.
+
 ### Manual command example: Wan2.2-I2V-A14B 720P
 
 ```bash
diff --git a/python/sglang/multimodal_gen/.claude/skills/sglang-diffusion-benchmark-profile/scripts/bench_diffusion_denoise.py b/python/sglang/multimodal_gen/.claude/skills/sglang-diffusion-benchmark-profile/scripts/bench_diffusion_denoise.py
index 002c13429..224462896 100755
--- a/python/sglang/multimodal_gen/.claude/skills/sglang-diffusion-benchmark-profile/scripts/bench_diffusion_denoise.py
+++ b/python/sglang/multimodal_gen/.claude/skills/sglang-diffusion-benchmark-profile/scripts/bench_diffusion_denoise.py
@@ -12,7 +12,7 @@ Usage:
     # Tag the run for later compare_perf.py usage
     python3 python/sglang/multimodal_gen/.claude/skills/sglang-diffusion-benchmark-profile/scripts/bench_diffusion_denoise.py --model flux --label tuned
 
-    # All 12 preset models
+    # All 14 preset models
     python3 python/sglang/multimodal_gen/.claude/skills/sglang-diffusion-benchmark-profile/scripts/bench_diffusion_denoise.py --all
 
     # Show preset order, model path, and nightly mapping
@@ -193,6 +193,39 @@ MODELS = {
         ],
     },
     # 10. Skill-only extra preset
+    "ltx23-one-stage": {
+        "path": "Lightricks/LTX-2.3",
+        "prompt": "A beautiful sunset over the ocean",
+        "negative_prompt": "shaky, glitchy, low quality, worst quality, deformed, distorted, disfigured, motion smear, motion artifacts, fused fingers, bad anatomy, weird hand, ugly, transition, static.",
+        "seed": 1234,
+        "extra_args": [
+            "--width=768",
+            "--height=512",
+            "--num-frames=121",
+            "--fps=24",
+            "--num-inference-steps=30",
+            "--guidance-scale=3.0",
+            "--num-gpus=2",
+        ],
+    },
+    # 11. Skill-only extra preset
+    "ltx23-two-stage": {
+        "path": "Lightricks/LTX-2.3",
+        "prompt": "A beautiful sunset over the ocean",
+        "negative_prompt": "shaky, glitchy, low quality, worst quality, deformed, distorted, disfigured, motion smear, motion artifacts, fused fingers, bad anatomy, weird hand, ugly, transition, static.",
+        "seed": 1234,
+        "extra_args": [
+            "--pipeline-class-name=LTX2TwoStagePipeline",
+            "--width=1536",
+            "--height=1024",
+            "--num-frames=121",
+            "--fps=24",
+            "--num-inference-steps=30",
+            "--guidance-scale=3.0",
+            "--num-gpus=2",
+        ],
+    },
+    # 12. Skill-only extra preset
     "hunyuanvideo": {
         "path": "hunyuanvideo-community/HunyuanVideo",
         "prompt": "A cat and a dog baking a cake together in a kitchen. The cat is carefully measuring flour, while the dog is stirring the batter with a wooden spoon. The kitchen is cozy, with sunlight streaming through the window.",
@@ -205,7 +238,7 @@ MODELS = {
             "--num-inference-steps=30",
         ],
     },
-    # 11. Skill-only extra preset
+    # 13. Skill-only extra preset
     # Requires: <repo>/inputs/diffusion_benchmark/figs/mova_single_person.jpg
     "mova-720p": {
         "path": "OpenMOSS-Team/MOVA-720p",
@@ -221,7 +254,7 @@ MODELS = {
             "--num-inference-steps=2",
         ],
     },
-    # 12. Skill-only extra preset
+    # 14. Skill-only extra preset
     "helios": {
         "path": "BestWishYsh/Helios-Base",
         "prompt": "A curious raccoon",
@@ -247,6 +280,8 @@ def required_gpus_for_model(model_key: str) -> int:
         return 4
     if model_key == "mova-720p":
         return 4
+    if model_key in {"ltx23-one-stage", "ltx23-two-stage"}:
+        return 2
     return 1
 
 
@@ -260,11 +295,11 @@ def print_model_catalog():
     print("=" * 95)
     print("MODEL PRESETS — Nightly-aligned first, skill-only extras after")
     print("=" * 95)
-    print(f"{'Preset':<14} {'Nightly':<28} {'Model Path':<46} {'GPUs':>4}")
+    print(f"{'Preset':<17} {'Nightly':<28} {'Model Path':<46} {'GPUs':>4}")
     print("-" * 95)
     for model_key, cfg in MODELS.items():
         print(
-            f"{model_key:<14} {model_nightly_case_id(model_key):<28} {cfg['path']:<46} {required_gpus_for_model(model_key):>4}"
+            f"{model_key:<17} {model_nightly_case_id(model_key):<28} {cfg['path']:<46} {required_gpus_for_model(model_key):>4}"
         )
     print("-" * 112)
     print(
@@ -474,7 +509,7 @@ def main():
         choices=list(MODELS.keys()),
         help="Model to benchmark (default: flux)",
     )
-    parser.add_argument("--all", action="store_true", help="Benchmark all 12 models")
+    parser.add_argument("--all", action="store_true", help="Benchmark all 14 models")
     parser.add_argument(
         "--list-models",
         action="store_true",
diff --git a/python/sglang/multimodal_gen/.claude/skills/sglang-diffusion-performance/SKILL.md b/python/sglang/multimodal_gen/.claude/skills/sglang-diffusion-performance/SKILL.md
index e81449004..5c8d91e01 100644
--- a/python/sglang/multimodal_gen/.claude/skills/sglang-diffusion-performance/SKILL.md
+++ b/python/sglang/multimodal_gen/.claude/skills/sglang-diffusion-performance/SKILL.md
@@ -88,6 +88,37 @@ sglang generate --model-path Lightricks/LTX-2 \
 
 Note: this generate recipe is aligned with the nightly comparison case `ltx2_twostage_t2v`. After [PR #20707](https://github.com/sgl-project/sglang/pull/20707), `LTX2TwoStagePipeline` is a native path and auto-resolves the spatial upsampler plus distilled LoRA from the same model snapshot unless you override them.
 
+### Native baseline, 2 GPUs: LTX-2.3 one-stage
+
+```bash
+sglang generate --model-path Lightricks/LTX-2.3 \
+  --prompt "A beautiful sunset over the ocean" \
+  --negative-prompt "shaky, glitchy, low quality, worst quality, deformed, distorted, disfigured, motion smear, motion artifacts, fused fingers, bad anatomy, weird hand, ugly, transition, static." \
+  --width 768 --height 512 \
+  --num-frames 121 --fps 24 \
+  --num-inference-steps 30 --guidance-scale 3.0 \
+  --seed 1234 --num-gpus 2 \
+  --enable-torch-compile --warmup --save-output
+```
+
+Note: use this as the native `LTX2Pipeline` baseline for `LTX-2.3`. It keeps the validated one-stage resolution and explicit `LTX-2.3` sampling defaults, and matches the `ltx23-one-stage` benchmark preset in `sglang-diffusion-benchmark-profile`.
+
+### Benchmark target, 2 GPUs: LTX-2.3 two-stage
+
+```bash
+sglang generate --model-path Lightricks/LTX-2.3 \
+  --pipeline-class-name LTX2TwoStagePipeline \
+  --prompt "A beautiful sunset over the ocean" \
+  --negative-prompt "shaky, glitchy, low quality, worst quality, deformed, distorted, disfigured, motion smear, motion artifacts, fused fingers, bad anatomy, weird hand, ugly, transition, static." \
+  --width 1536 --height 1024 \
+  --num-frames 121 --fps 24 \
+  --num-inference-steps 30 --guidance-scale 3.0 \
+  --seed 1234 --num-gpus 2 \
+  --enable-torch-compile --warmup --save-output
+```
+
+Note: this is the recommended benchmark command for the new `LTX-2.3` two-stage path. It uses the native `LTX2TwoStagePipeline` and matches the `ltx23-two-stage` benchmark preset in `sglang-diffusion-benchmark-profile`.
+
 ### Maximum speed, image model, single GPU, lossless
 
 ```bash