[XPU] Add diffusion server test config for Intel XPU B60

python/sglang/multimodal_gen/test/server/consistency_thresholds/intel_xpu_b60.json

@@ -0,0 +1,17 @@
+{
+  "_comment": "Consistency thresholds for Intel Arc Pro B60 (XPU). The GT images are CUDA-generated, and XPU seeds its initial latent noise from a different RNG stream, so pixels cannot match: the image is semantically identical (CLIP stays high) while ssim/psnr/mean_abs_diff degrade. Per-case entries below are only tuned where an XPU run has actually been measured; the rest are inherited from h100.json and will need the same treatment as they are triaged.",
+  "cases": {
+    "qwen_image_t2i_2_gpus": {
+      "clip_threshold": 0.98,
+      "ssim_threshold": 0.79,
+      "psnr_threshold": 15.7,
+      "mean_abs_diff_threshold": 17.2
+    },
+    "fsdp-inference": {
+      "clip_threshold": 0.97,
+      "ssim_threshold": 0.6,
+      "psnr_threshold": 11.0,
+      "mean_abs_diff_threshold": 37.0
+    }
+  }
+}

python/sglang/multimodal_gen/test/server/testcase_configs.py

@@ -951,4 +951,5 @@ def _with_default_num_gpus(
     BaselineConfig.load(get_perf_baseline_path())
     .update(Path(__file__).parent / "ascend" / "perf_baselines_npu.json")
     .update(Path(__file__).parent / "musa" / "perf_baselines_musa.json")
+    .update(Path(__file__).parent / "xpu" / "perf_baselines_xpu.json")
 )

python/sglang/multimodal_gen/test/server/xpu/perf_baselines_xpu.json

@@ -0,0 +1,34 @@
+{
+  "metadata": {
+    "model": "Diffusion Server",
+    "hardware": "Intel Arc Pro B60 (22.71 GiB per card)",
+    "description": "Reference numbers captured on XPU; these override the CUDA baselines only when running on XPU, since XPU reuses the shared case ids"
+  },
+  "scenarios": {
+    "fsdp-inference": {
+      "stages_ms": {
+        "InputValidationStage": 0.04,
+        "TextEncodingStage": 822.67,
+        "LatentPreparationStage": 0.21,
+        "TimestepPreparationStage": 34933.02,
+        "DenoisingStage": 9091.12,
+        "DecodingStage": 17.8
+      },
+      "denoise_step_ms": {
+        "0": 285.12,
+        "1": 1096.41,
+        "2": 1091.69,
+        "3": 1098.41,
+        "4": 1124.7,
+        "5": 1099.74,
+        "6": 1100.13,
+        "7": 1095.65,
+        "8": 1094.18
+      },
+      "expected_e2e_ms": 44870.65,
+      "expected_avg_denoise_ms": 1009.56,
+      "expected_median_denoise_ms": 1096.41,
+      "estimated_full_test_time_s": 157.0
+    }
+  }
+}

python/sglang/multimodal_gen/test/test_utils.py

@@ -80,6 +80,7 @@
     "h100": "h100.json",
     "b200": "b200.json",
     "5090": "5090.json",
+    "intel_xpu_b60": "intel_xpu_b60.json",
 }
 CONSISTENCY_PLATFORM_ALIASES = {
     "sm90": "h100",
@@ -91,6 +92,7 @@
     "sm120": "5090",
     "rtx5090": "5090",
     "5090": "5090",
+    "intelxpub60": "intel_xpu_b60",
 }
 CLIP_MODEL_NAME = "openai/clip-vit-large-patch14"
 DEFAULT_CLIP_THRESHOLD_IMAGE = 0.92
@@ -903,6 +905,8 @@ def get_consistency_platform() -> str:
         return "5090"
     if current_platform.is_blackwell():
         return "b200"
+    if current_platform.is_xpu():
+        return "intel_xpu_b60"
     return "h100"