Finally FLUX NVFP4 quantization working

examples/diffusers/quantization/config.py

@@ -13,6 +13,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import copy
 import torch.nn as nn
 from calib.plugin_calib import PercentileCalibrator
 
@@ -98,6 +99,38 @@
     "algorithm": {"method": "svdquant", "lowrank": 32},
 }
 
+# FLUX Dev mixed-format layers derived from official NVFP4 metadata.
+# These patterns target diffusers module names (pre-export), not ComfyUI names.
+FLUX_DEV_FP8_LAYER_PATTERNS = [
+    "transformer_blocks.*.attn.to_q",
+    "transformer_blocks.*.attn.to_k",
+    "transformer_blocks.*.attn.to_v",
+    "transformer_blocks.*.attn.add_q_proj",
+    "transformer_blocks.*.attn.add_k_proj",
+    "transformer_blocks.*.attn.add_v_proj",
+    "transformer_blocks.*.norm1.linear",
+    "transformer_blocks.*.norm1_context.linear",
+    "single_transformer_blocks.*.norm.linear",
+]
+
+
+def _build_flux_dev_nvfp4_mixed_config():
+    cfg = copy.deepcopy(NVFP4_FP8_MHA_CONFIG)
+    quant_cfg = cfg["quant_cfg"]
+    fp8_override = {
+        "num_bits": (4, 3),
+        "axis": None,
+        "block_sizes": None,
+        "enable": True,
+    }
+    for layer_pattern in FLUX_DEV_FP8_LAYER_PATTERNS:
+        quant_cfg[f"*{layer_pattern}*weight_quantizer*"] = fp8_override
+        quant_cfg[f"*{layer_pattern}*input_quantizer*"] = fp8_override
+    return cfg
+
+
+FLUX_DEV_NVFP4_MIXED_CONFIG = _build_flux_dev_nvfp4_mixed_config()
+
 
 def set_quant_config_attr(quant_config, trt_high_precision_dtype, quant_algo, **kwargs):
     algo_cfg = {"method": quant_algo}