diff --git a/README.md b/README.md
index 940e44d0..22bcc473 100644
--- a/README.md
+++ b/README.md
@@ -73,8 +73,8 @@ Ethos-U version info:
     Arch:       v2.0.0
     MACs/cc:    256
     Cmd stream: v1
-ExecuTorch Ethos-U85 example: 8784 byte model
-Output: 10 element(s): 0.0079 0.0459 0.0475 -0.0475 0.0791 0.0411 -0.0285 -0.0744 -0.2246 -0.0016
+ExecuTorch Ethos-U85 example: 8720 byte model
+Output: 10 element(s): -0.0142 0.0206 0.0601 -0.0886 0.0791 0.0522 -0.0301 -0.0775 -0.2800 -0.0095
 Test_result: PASS
 ```
 
@@ -211,6 +211,11 @@ fixed shape and prints the output as ten floats, so a model with another input
 shape or output needs matching changes there. Then re-run `create_ai_layer.py`
 and build.
 
+Give an image model its input as NHWC, the layout of a camera frame, as
+`model/model.py` does: the model permutes it to the NCHW its convolutions take,
+and Vela folds that into the first convolution. With an NCHW input the NPU
+first reorders the image in an operation of its own.
+
 To target another Ethos-U configuration, update the target and `mlops:`
 settings in the CMSIS solution and re-run all three steps. The generated Vela
 options then follow that configuration automatically; `vela: misc:` takes any
diff --git a/ai_layer/model_pte.c b/ai_layer/model_pte.c
index 6de9411d..75bd1634 100644
--- a/ai_layer/model_pte.c
+++ b/ai_layer/model_pte.c
@@ -3,78 +3,74 @@ __attribute__((aligned(16))) const unsigned char model_pte[] = {
   0x24, 0x00, 0x00, 0x00, 0x45, 0x54, 0x31, 0x32, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
   0x00, 0x00, 0x00, 0x00, 0x10, 0x00, 0x18, 0x00, 0x00, 0x00, 0x14, 0x00, 0x10, 0x00, 0x0c, 0x00,
   0x08, 0x00, 0x04, 0x00, 0x10, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x24, 0x00, 0x00, 0x00,
-  0x2c, 0x00, 0x00, 0x00, 0x8c, 0x1a, 0x00, 0x00, 0x8c, 0x1a, 0x00, 0x00, 0x20, 0xe2, 0xff, 0xff,
+  0x2c, 0x00, 0x00, 0x00, 0x4c, 0x1a, 0x00, 0x00, 0x4c, 0x1a, 0x00, 0x00, 0x60, 0xe2, 0xff, 0xff,
   0x04, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
-  0x01, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x50, 0xe0, 0xff, 0xff, 0x01, 0x00, 0x00, 0x00,
-  0x04, 0x00, 0x00, 0x00, 0xa2, 0xdf, 0xff, 0xff, 0x04, 0x00, 0x00, 0x00, 0x50, 0x1a, 0x00, 0x00,
+  0x01, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x90, 0xe0, 0xff, 0xff, 0x01, 0x00, 0x00, 0x00,
+  0x04, 0x00, 0x00, 0x00, 0xe2, 0xdf, 0xff, 0xff, 0x04, 0x00, 0x00, 0x00, 0x10, 0x1a, 0x00, 0x00,
   0x76, 0x65, 0x6c, 0x61, 0x5f, 0x62, 0x69, 0x6e, 0x5f, 0x73, 0x74, 0x72, 0x65, 0x61, 0x6d, 0x00,
   0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
   0x63, 0x6d, 0x64, 0x5f, 0x64, 0x61, 0x74, 0x61, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
-  0x00, 0x04, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
+  0xb4, 0x03, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
   0x43, 0x4f, 0x50, 0x31, 0x01, 0x00, 0x10, 0x00, 0x18, 0x01, 0x00, 0x20, 0x00, 0x70, 0x00, 0x20,
-  0x05, 0x00, 0x00, 0x00, 0x05, 0x00, 0x00, 0x00, 0x05, 0x00, 0x00, 0x00, 0x02, 0x00, 0xf8, 0x00,
+  0x05, 0x00, 0x00, 0x00, 0x05, 0x00, 0x00, 0x00, 0x05, 0x00, 0x00, 0x00, 0x02, 0x00, 0xe5, 0x00,
+  0x30, 0x01, 0x00, 0x00, 0x30, 0x40, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x31, 0x01, 0x01, 0x00,
+  0x31, 0x40, 0x00, 0x00, 0x00, 0x13, 0x00, 0x00, 0x32, 0x40, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00,
+  0x32, 0x01, 0x01, 0x00, 0x10, 0x00, 0x00, 0x00, 0x24, 0x40, 0x22, 0x20, 0x23, 0x72, 0xc9, 0x02,
   0x05, 0x01, 0x01, 0x00, 0x0f, 0x01, 0x01, 0x00, 0x00, 0x40, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00,
   0x01, 0x40, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x02, 0x40, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
-  0x03, 0x40, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0b, 0x01, 0x02, 0x00, 0x0c, 0x01, 0x02, 0x00,
-  0x0a, 0x01, 0x0f, 0x00, 0x04, 0x01, 0x0f, 0x00, 0x05, 0x40, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00,
-  0x04, 0x40, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x06, 0x40, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
-  0x09, 0x01, 0x00, 0x00, 0x07, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x01, 0x01, 0x00, 0x00,
-  0x03, 0x01, 0x00, 0x00, 0x02, 0x01, 0x00, 0x00, 0x14, 0x01, 0x41, 0x19, 0x1f, 0x01, 0x01, 0x00,
+  0x03, 0x40, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0b, 0x01, 0x0f, 0x00, 0x0c, 0x01, 0x0f, 0x00,
+  0x0a, 0x01, 0x0f, 0x00, 0x04, 0x01, 0x02, 0x00, 0x05, 0x40, 0x00, 0x00, 0x30, 0x00, 0x00, 0x00,
+  0x04, 0x40, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x06, 0x40, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
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   0x10, 0x40, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x40, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
   0x12, 0x40, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x13, 0x40, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
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   0x1c, 0x01, 0x0f, 0x00, 0x1a, 0x01, 0x0f, 0x00, 0x15, 0x40, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00,
   0x14, 0x40, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x16, 0x40, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00,
-  0x18, 0x01, 0x00, 0x00, 0x21, 0x01, 0x00, 0x00, 0x20, 0x01, 0x00, 0x00, 0x22, 0x01, 0x00, 0x00,
-  0x25, 0x01, 0x00, 0x00, 0x26, 0x01, 0x80, 0xff, 0x27, 0x01, 0x7f, 0x00, 0x24, 0x40, 0x00, 0x00,
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-  0x24, 0x01, 0x00, 0x01, 0x2f, 0x01, 0x00, 0x00, 0x05, 0x00, 0x03, 0x00, 0x30, 0x01, 0x00, 0x00,
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+  0x80, 0x00, 0x00, 0x00, 0x16, 0x40, 0x00, 0x00, 0x80, 0x00, 0x00, 0x00, 0x18, 0x01, 0x00, 0x00,
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-  0x04, 0x40, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x06, 0x40, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
-  0x09, 0x01, 0x80, 0xff, 0x14, 0x01, 0x01, 0x00, 0x10, 0x40, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00,
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-  0x1c, 0x01, 0x00, 0x00, 0x1a, 0x01, 0x00, 0x00, 0x15, 0x40, 0x00, 0x00, 0x0a, 0x00, 0x00, 0x00,
-  0x14, 0x40, 0x00, 0x00, 0x0a, 0x00, 0x00, 0x00, 0x18, 0x01, 0x4d, 0x00, 0x21, 0x01, 0x00, 0x00,
-  0x20, 0x01, 0x00, 0x00, 0x22, 0x01, 0x00, 0x00, 0x20, 0x40, 0x00, 0x00, 0x00, 0x09, 0x00, 0x00,
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+  0x01, 0x00, 0x00, 0x00, 0x15, 0x01, 0x07, 0x00, 0x24, 0x01, 0x00, 0x01, 0x05, 0x00, 0x00, 0x00,
+  0x24, 0x40, 0x28, 0x20, 0xc1, 0xc4, 0x79, 0x61, 0x00, 0x40, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00,
+  0x0b, 0x01, 0x07, 0x00, 0x0c, 0x01, 0x07, 0x00, 0x0a, 0x01, 0x07, 0x00, 0x05, 0x40, 0x00, 0x00,
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+  0x00, 0x01, 0x01, 0x00, 0x01, 0x01, 0x01, 0x00, 0x03, 0x01, 0x01, 0x00, 0x02, 0x01, 0x01, 0x00,
+  0x14, 0x01, 0x41, 0x00, 0x10, 0x40, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x13, 0x01, 0x0f, 0x00,
+  0x18, 0x01, 0x80, 0xff, 0x21, 0x01, 0x02, 0x00, 0x20, 0x01, 0x02, 0x00, 0x22, 0x01, 0x04, 0x00,
+  0x28, 0x01, 0x00, 0x00, 0x20, 0x40, 0x00, 0x00, 0xa0, 0x02, 0x00, 0x00, 0x21, 0x40, 0x00, 0x00,
+  0xc0, 0x05, 0x00, 0x00, 0x29, 0x01, 0x00, 0x00, 0x22, 0x40, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00,
+  0x24, 0x01, 0x00, 0x02, 0x02, 0x00, 0x00, 0x00, 0x00, 0x40, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
+  0x04, 0x01, 0x0f, 0x00, 0x09, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x01, 0x01, 0x00, 0x00,
+  0x03, 0x01, 0x00, 0x00, 0x02, 0x01, 0x00, 0x00, 0x14, 0x01, 0x01, 0x31, 0x10, 0x40, 0x00, 0x00,
+  0x00, 0x04, 0x00, 0x00, 0x12, 0x01, 0x03, 0x00, 0x11, 0x01, 0x03, 0x00, 0x1b, 0x01, 0x0f, 0x00,
+  0x1c, 0x01, 0x0f, 0x00, 0x1a, 0x01, 0x03, 0x00, 0x15, 0x40, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00,
+  0x14, 0x40, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x16, 0x40, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
+  0x18, 0x01, 0x00, 0x00, 0x21, 0x01, 0x01, 0x00, 0x20, 0x01, 0x01, 0x00, 0x22, 0x01, 0x03, 0x00,
+  0x24, 0x40, 0x00, 0x20, 0x01, 0x00, 0x00, 0x00, 0x16, 0x01, 0x03, 0x00, 0x15, 0x01, 0x03, 0x00,
+  0x24, 0x01, 0x00, 0x01, 0x05, 0x00, 0x00, 0x00, 0x24, 0x40, 0x29, 0x20, 0x3b, 0xa1, 0x86, 0x34,
+  0x05, 0x01, 0x01, 0x00, 0x00, 0x40, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x0b, 0x01, 0x00, 0x00,
+  0x0c, 0x01, 0x00, 0x00, 0x0a, 0x01, 0x00, 0x00, 0x04, 0x01, 0xff, 0x00, 0x05, 0x40, 0x00, 0x00,
+  0x00, 0x01, 0x00, 0x00, 0x04, 0x40, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x06, 0x40, 0x00, 0x00,
+  0x01, 0x00, 0x00, 0x00, 0x09, 0x01, 0x80, 0xff, 0x14, 0x01, 0x01, 0x00, 0x10, 0x40, 0x00, 0x00,
+  0x00, 0x00, 0x00, 0x00, 0x12, 0x01, 0x00, 0x00, 0x11, 0x01, 0x00, 0x00, 0x13, 0x01, 0x09, 0x00,
+  0x1b, 0x01, 0x00, 0x00, 0x1c, 0x01, 0x00, 0x00, 0x1a, 0x01, 0x00, 0x00, 0x15, 0x40, 0x00, 0x00,
+  0x0a, 0x00, 0x00, 0x00, 0x14, 0x40, 0x00, 0x00, 0x0a, 0x00, 0x00, 0x00, 0x18, 0x01, 0x4d, 0x00,
+  0x21, 0x01, 0x00, 0x00, 0x20, 0x01, 0x00, 0x00, 0x22, 0x01, 0x00, 0x00, 0x20, 0x40, 0x00, 0x00,
+  0x00, 0x09, 0x00, 0x00, 0x21, 0x40, 0x00, 0x00, 0x00, 0x0c, 0x00, 0x00, 0x22, 0x40, 0x00, 0x00,
+  0x60, 0x08, 0x00, 0x00, 0x16, 0x01, 0x00, 0x00, 0x24, 0x01, 0x00, 0x02, 0x02, 0x00, 0x00, 0x00,
+  0x00, 0x00, 0xff, 0xff, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
   0x77, 0x65, 0x69, 0x67, 0x68, 0x74, 0x5f, 0x64, 0x61, 0x74, 0x61, 0x00, 0x00, 0x00, 0x00, 0x00,
   0x00, 0x15, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
   0x5f, 0x98, 0xff, 0xff, 0x23, 0x72, 0xc9, 0x02, 0x22, 0x00, 0x45, 0xbd, 0xff, 0xff, 0xb9, 0x1d,
@@ -109,16 +105,16 @@ __attribute__((aligned(16))) const unsigned char model_pte[] = {
   0x14, 0x63, 0xf4, 0x94, 0xc4, 0xc2, 0x40, 0x9a, 0xbb, 0x12, 0x12, 0xfe, 0xa7, 0x91, 0xa9, 0x17,
   0x37, 0x1f, 0x53, 0x1b, 0x49, 0xfe, 0x3f, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff,
   0x0f, 0xf0, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff,
-  0x68, 0x13, 0x00, 0x00, 0x9f, 0x71, 0x5e, 0x18, 0x26, 0x00, 0x01, 0x4b, 0x00, 0x00, 0xd1, 0xbb,
-  0x93, 0x18, 0x26, 0x00, 0x80, 0xe5, 0xff, 0xff, 0xef, 0x3d, 0x28, 0x31, 0x27, 0x00, 0xa0, 0x3a,
-  0x00, 0x00, 0x19, 0xbb, 0xe0, 0x30, 0x27, 0x00, 0xdd, 0xeb, 0x00, 0x00, 0xc3, 0x94, 0x2d, 0x62,
-  0x28, 0x00, 0x35, 0x62, 0xff, 0xff, 0x0b, 0x5b, 0xf4, 0x5f, 0x28, 0x00, 0xb3, 0xf2, 0xff, 0xff,
-  0x15, 0xe2, 0x05, 0x30, 0x27, 0x00, 0x06, 0xa5, 0xff, 0xff, 0x2d, 0xdb, 0x45, 0x0c, 0x25, 0x00,
-  0xf4, 0xd1, 0x00, 0x00, 0x67, 0xa2, 0xe5, 0x30, 0x27, 0x00, 0xb7, 0xcb, 0x00, 0x00, 0x49, 0x9e,
-  0x54, 0x62, 0x28, 0x00, 0x7f, 0xf9, 0xff, 0xff, 0x07, 0x61, 0x1f, 0x62, 0x28, 0x00, 0x0e, 0xad,
-  0xff, 0xff, 0x31, 0x8e, 0x72, 0x18, 0x26, 0x00, 0x69, 0x6c, 0xff, 0xff, 0xf9, 0xbd, 0x3e, 0x0c,
-  0x25, 0x00, 0xb6, 0xac, 0x00, 0x00, 0xdd, 0x24, 0xf2, 0x60, 0x28, 0x00, 0x85, 0xef, 0xff, 0xff,
-  0xbb, 0x83, 0xc8, 0x61, 0x28, 0x00, 0x4b, 0xe3, 0x00, 0x00, 0xa9, 0x82, 0x3d, 0x18, 0x26, 0x00,
+  0x68, 0x13, 0x00, 0x00, 0xc1, 0xc4, 0x79, 0x61, 0x28, 0x00, 0x01, 0x4b, 0x00, 0x00, 0x85, 0xed,
+  0x4e, 0x62, 0x28, 0x00, 0x80, 0xe5, 0xff, 0xff, 0x1f, 0x7a, 0x50, 0x62, 0x28, 0x00, 0xa0, 0x3a,
+  0x00, 0x00, 0x3b, 0xba, 0xe0, 0x30, 0x27, 0x00, 0xdd, 0xeb, 0x00, 0x00, 0x05, 0x93, 0x2d, 0x62,
+  0x28, 0x00, 0x35, 0x62, 0xff, 0xff, 0x57, 0x59, 0xf4, 0x5f, 0x28, 0x00, 0xb3, 0xf2, 0xff, 0xff,
+  0x3b, 0xe1, 0x05, 0x30, 0x27, 0x00, 0x06, 0xa5, 0xff, 0xff, 0xa9, 0xd7, 0x2e, 0x62, 0x28, 0x00,
+  0xf4, 0xd1, 0x00, 0x00, 0x89, 0xa1, 0xe5, 0x30, 0x27, 0x00, 0xb7, 0xcb, 0x00, 0x00, 0x45, 0x4e,
+  0x2a, 0x31, 0x27, 0x00, 0x7f, 0xf9, 0xff, 0xff, 0x49, 0x5f, 0x1f, 0x62, 0x28, 0x00, 0x0e, 0xad,
+  0xff, 0xff, 0x07, 0x37, 0xca, 0x61, 0x28, 0x00, 0x69, 0x6c, 0xff, 0xff, 0x05, 0xf7, 0xfa, 0x30,
+  0x27, 0x00, 0xb6, 0xac, 0x00, 0x00, 0x25, 0x23, 0xf2, 0x60, 0x28, 0x00, 0x85, 0xef, 0xff, 0xff,
+  0xff, 0x81, 0xc8, 0x61, 0x28, 0x00, 0x4b, 0xe3, 0x00, 0x00, 0xeb, 0x08, 0xf6, 0x60, 0x28, 0x00,
   0xc8, 0x23, 0x5c, 0x01, 0x0c, 0x00, 0xdd, 0xe4, 0x51, 0x20, 0x93, 0x44, 0x1d, 0x4a, 0x00, 0xe0,
   0xba, 0xeb, 0x25, 0xc1, 0x9f, 0x95, 0x85, 0x03, 0x00, 0xad, 0xce, 0x82, 0xa8, 0x66, 0x08, 0x0c,
   0x5c, 0xf5, 0xe5, 0xcb, 0xa9, 0xd9, 0xc2, 0xd4, 0x96, 0x00, 0x50, 0xd4, 0xc3, 0xef, 0xd2, 0x75,
@@ -211,13 +207,13 @@ __attribute__((aligned(16))) const unsigned char model_pte[] = {
   0x9a, 0xfa, 0x0d, 0x00, 0x35, 0xfc, 0xd3, 0x31, 0x9c, 0xfc, 0xea, 0x65, 0xf0, 0xbf, 0xcb, 0x9c,
   0xc0, 0xb2, 0x44, 0x04, 0x71, 0xf5, 0xff, 0x78, 0x2a, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff,
   0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0x0f, 0xf0,
-  0xbb, 0xf7, 0xfe, 0xff, 0x8d, 0xa0, 0x86, 0x34, 0x29, 0x00, 0xd8, 0x70, 0x01, 0x00, 0xa7, 0x3f,
-  0x36, 0x34, 0x29, 0x00, 0x56, 0x05, 0x01, 0x00, 0x81, 0x58, 0xbc, 0x68, 0x2a, 0x00, 0x31, 0xf9,
-  0xfe, 0xff, 0xcf, 0xea, 0xef, 0x68, 0x2a, 0x00, 0xcb, 0xa8, 0x00, 0x00, 0x49, 0x3e, 0x33, 0x34,
-  0x29, 0x00, 0x2c, 0x9e, 0x00, 0x00, 0xcd, 0x98, 0x1a, 0x69, 0x2a, 0x00, 0x94, 0xeb, 0xfe, 0xff,
-  0x1d, 0x76, 0x82, 0x34, 0x29, 0x00, 0x8d, 0xf0, 0xfe, 0xff, 0x4b, 0x61, 0xbe, 0x68, 0x2a, 0x00,
-  0x4c, 0xc0, 0xfe, 0xff, 0x5b, 0xfb, 0xc7, 0x68, 0x2a, 0x00, 0x15, 0xac, 0x00, 0x00, 0xeb, 0x67,
-  0x2e, 0x1a, 0x28, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
+  0xbb, 0xf7, 0xfe, 0xff, 0x3b, 0xa1, 0x86, 0x34, 0x29, 0x00, 0xd8, 0x70, 0x01, 0x00, 0x15, 0x90,
+  0x0d, 0x0d, 0x27, 0x00, 0x56, 0x05, 0x01, 0x00, 0x77, 0x16, 0x2f, 0x1a, 0x28, 0x00, 0x31, 0xf9,
+  0xfe, 0xff, 0x2b, 0xec, 0xef, 0x68, 0x2a, 0x00, 0xcb, 0xa8, 0x00, 0x00, 0x7b, 0x9f, 0x19, 0x1a,
+  0x28, 0x00, 0x2c, 0x9e, 0x00, 0x00, 0x45, 0x53, 0x23, 0x0d, 0x27, 0x00, 0x94, 0xeb, 0xfe, 0xff,
+  0xcb, 0x76, 0x82, 0x34, 0x29, 0x00, 0x8d, 0xf0, 0xfe, 0xff, 0x53, 0x31, 0x5f, 0x34, 0x29, 0x00,
+  0x4c, 0xc0, 0xfe, 0xff, 0x5b, 0xfe, 0x63, 0x34, 0x29, 0x00, 0x15, 0xac, 0x00, 0x00, 0x07, 0xa1,
+  0xb9, 0x68, 0x2a, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
   0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
   0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
   0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
@@ -415,17 +411,17 @@ __attribute__((aligned(16))) const unsigned char model_pte[] = {
   0xff, 0x84, 0x38, 0xff, 0xff, 0xff, 0x0f, 0xf0, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff,
   0x73, 0x63, 0x72, 0x61, 0x74, 0x63, 0x68, 0x5f, 0x73, 0x69, 0x7a, 0x65, 0x00, 0x00, 0x00, 0x00,
   0x04, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
-  0x00, 0x22, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
+  0x00, 0x15, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
   0x69, 0x6e, 0x70, 0x75, 0x74, 0x73, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
   0x28, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
   0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
-  0x03, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
+  0x10, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
   0x00, 0x10, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
   0x6f, 0x75, 0x74, 0x70, 0x75, 0x74, 0x73, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
   0x28, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
   0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
   0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x0a, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
-  0x00, 0x01, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
+  0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
   0x76, 0x65, 0x6c, 0x61, 0x5f, 0x65, 0x6e, 0x64, 0x5f, 0x73, 0x74, 0x72, 0x65, 0x61, 0x6d, 0x00,
   0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
   0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x1c, 0x00, 0x00, 0x00, 0x00, 0x00, 0x16, 0x00,
@@ -498,7 +494,7 @@ __attribute__((aligned(16))) const unsigned char model_pte[] = {
   0x00, 0x00, 0x00, 0x02, 0x32, 0xfe, 0xff, 0xff, 0x80, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff,
   0xf0, 0xfe, 0xff, 0xff, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x02, 0x4a, 0xfe, 0xff, 0xff,
   0x4d, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x08, 0xff, 0xff, 0xff, 0x08, 0x00, 0x00, 0x00,
-  0x00, 0x00, 0x00, 0x04, 0x62, 0xfe, 0xff, 0xff, 0x00, 0x00, 0x00, 0x20, 0x31, 0xeb, 0x59, 0x3f,
+  0x00, 0x00, 0x00, 0x04, 0x62, 0xfe, 0xff, 0xff, 0x00, 0x00, 0x00, 0x40, 0x31, 0xeb, 0x59, 0x3f,
   0x00, 0x00, 0x00, 0x00, 0x24, 0xff, 0xff, 0xff, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x05,
   0x02, 0xff, 0xff, 0xff, 0x10, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00,
   0x00, 0x00, 0x00, 0x06, 0x92, 0xfe, 0xff, 0xff, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00,
@@ -520,13 +516,13 @@ __attribute__((aligned(16))) const unsigned char model_pte[] = {
   0x12, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00, 0x1c, 0x00, 0x00, 0x00,
   0x00, 0x00, 0x00, 0x01, 0x78, 0xff, 0xff, 0xff, 0x00, 0x0c, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
   0x04, 0x00, 0x00, 0x00, 0x00, 0x01, 0x02, 0x03, 0x04, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
-  0x03, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0a, 0x00,
+  0x10, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0a, 0x00,
   0x09, 0x00, 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00, 0x00, 0x05, 0x12, 0x00,
   0x12, 0x00, 0x11, 0x00, 0x00, 0x00, 0x0c, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x04, 0x00,
   0x12, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00, 0x1c, 0x00, 0x00, 0x00,
   0x00, 0x06, 0x06, 0x00, 0x08, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
   0x04, 0x00, 0x00, 0x00, 0x00, 0x01, 0x02, 0x03, 0x04, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
-  0x03, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0c, 0x00,
+  0x10, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0c, 0x00,
   0x08, 0x00, 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x44, 0x00, 0x00, 0x00,
   0x39, 0x00, 0x00, 0x00, 0x5b, 0x31, 0x2c, 0x20, 0x7b, 0x22, 0x74, 0x79, 0x70, 0x65, 0x22, 0x3a,
   0x20, 0x6e, 0x75, 0x6c, 0x6c, 0x2c, 0x20, 0x22, 0x63, 0x6f, 0x6e, 0x74, 0x65, 0x78, 0x74, 0x22,
diff --git a/model/model.py b/model/model.py
index d9d54a64..8af0e024 100644
--- a/model/model.py
+++ b/model/model.py
@@ -4,19 +4,22 @@
 
 Small enough to export in seconds and fully partition onto the NPU, but real
 enough to exercise conv / relu / pool / linear through Vela. Input is a single
-16x16 RGB image (NCHW); output is a 10-class logit vector.
+16x16 RGB image (NHWC); output is a 10-class logit vector.
 """
 
 import torch
 from torch import nn
 
-INPUT_SHAPE = (1, 3, 16, 16)
+# NHWC, the layout of a camera frame, which the Ethos-U reads as it is. An NCHW
+# input costs one more NPU operation that reorders it before the first
+# convolution.
+INPUT_SHAPE = (1, 16, 16, 3)
 
 
 class TinyCNN(nn.Module):
     def __init__(self, input_shape: tuple[int, ...] = INPUT_SHAPE, num_classes: int = 10) -> None:
         super().__init__()
-        _, channels, height, width = input_shape
+        _, height, width, channels = input_shape
         self.features = nn.Sequential(
             nn.Conv2d(channels, 8, kernel_size=3, padding=1),
             nn.ReLU(),
@@ -28,7 +31,8 @@ def __init__(self, input_shape: tuple[int, ...] = INPUT_SHAPE, num_classes: int
         self.classifier = nn.Linear(16 * (height // 4) * (width // 4), num_classes)
 
     def forward(self, x: torch.Tensor) -> torch.Tensor:
-        x = self.features(x)
+        # The convolutions take NCHW. Vela folds the permutation into the first one.
+        x = self.features(x.permute(0, 3, 1, 2))
         x = torch.flatten(x, 1)
         return self.classifier(x)
 
diff --git a/src/app_main.cpp b/src/app_main.cpp
index 54d1e758..b7fc869f 100644
--- a/src/app_main.cpp
+++ b/src/app_main.cpp
@@ -71,14 +71,14 @@ extern "C" int app_main(void) {
       std::make_unique<MemoryAllocator>(kMethodPoolSize, g_method_pool),
       std::make_unique<MemoryAllocator>(kTempPoolSize, g_temp_pool));
 
-  // TinyCNN takes one 16x16 RGB image in NCHW order (see model/model.py),
+  // TinyCNN takes one 16x16 RGB image in NHWC order (see model/model.py),
   // filled here with a deterministic ramp. The tensor only wraps the buffer;
   // no tensor extension (and its std::random_device) is needed for that.
-  alignas(16) static float input_data[3 * 16 * 16];
+  alignas(16) static float input_data[16 * 16 * 3];
   for (size_t i = 0; i < sizeof(input_data) / sizeof(input_data[0]); ++i) {
     input_data[i] = static_cast<float>(i % 32) / 32.0f - 0.5f;
   }
-  std::array<SizesType, 4> sizes{1, 3, 16, 16};
+  std::array<SizesType, 4> sizes{1, 16, 16, 3};
   std::array<DimOrderType, 4> dim_order{0, 1, 2, 3};
   TensorImpl input_impl(ScalarType::Float, sizes.size(), sizes.data(), input_data, dim_order.data());
   Tensor input(&input_impl);