diff --git a/src/python/omnimalloc/benchmark/converters/model.py b/src/python/omnimalloc/benchmark/converters/model.py
index 7bbbb7e..eee1f7d 100644
--- a/src/python/omnimalloc/benchmark/converters/model.py
+++ b/src/python/omnimalloc/benchmark/converters/model.py
@@ -16,6 +16,8 @@
     "int4": 4,
     "uint4": 4,
     "float4_e2m1fn": 4,
+    "float6_e2m3fn": 6,
+    "float6_e3m2fn": 6,
     "bool": 8,
     "int8": 8,
     "uint8": 8,
diff --git a/tests/unit/benchmark/converters/test_onnx.py b/tests/unit/benchmark/converters/test_onnx.py
index 850fa12..f87bf31 100644
--- a/tests/unit/benchmark/converters/test_onnx.py
+++ b/tests/unit/benchmark/converters/test_onnx.py
@@ -70,7 +70,15 @@ def simple_onnx_model() -> "onnx.ModelProto":
 
 # The widths onnx.helper.make_tensor packs a raw tensor to, for the types numpy
 # has no storage for; every other type is one numpy itemsize per element.
-SUB_BYTE_BITS = {"INT2": 2, "UINT2": 2, "INT4": 4, "UINT4": 4, "FLOAT4E2M1": 4}
+SUB_BYTE_BITS = {
+    "INT2": 2,
+    "UINT2": 2,
+    "INT4": 4,
+    "UINT4": 4,
+    "FLOAT4E2M1": 4,
+    "FLOAT6E2M3": 6,
+    "FLOAT6E3M2": 6,
+}
 
 
 def test_itembits_covers_every_onnx_dtype() -> None: