And yes, I can confirm that it works in dedicated access mode. I've used following code:

pip install graphframes-py

from functools import reduce
from pyspark.sql import functions as F
from graphframes import GraphFrame

nodes = [
    (1, "Alice", 30),
    (2, "Bob", 25),
    (3, "Charlie", 35)
]
nodes_df = spark.createDataFrame(nodes, ["id", "name", "age"])

edges = [
    (1, 2, "friend"),
    (2, 1, "friend"),
    (2, 3, "friend"),
    (3, 2, "enemy")  # eek!
]
edges_df = spark.createDataFrame(edges, ["src", "dst", "relationship"])

g = GraphFrame(nodes_df, edges_df)

 And as you can see it works as expected:

One thing to remember, Python distribution does not include JVM-core. So I had to install also this version of library on my cluster : graphframes:graphframes:0.8.3-spark3.5-s_2.13