cursor.execute() with many bound parameters (~2000) is ~14x slower than pyodbc #500

import time
import mssql_python
import pyodbc

N = 100_000
COLS = 2
# ~1049 rows per INSERT, ~2098 params per call, ~95 calls total
ROWS_PER_BATCH = 2099 // COLS
SQL = "INSERT INTO bench (id, name) VALUES " + ",".join(
    [f"(?, ?)"] * ROWS_PER_BATCH
)
PARAMS = [None] * (ROWS_PER_BATCH * COLS)

# --- mssql-python ---
conn = mssql_python.connect(
    "SERVER=localhost;DATABASE=master;UID=sa;PWD=YourPassword;"
    "Encrypt=yes;TrustServerCertificate=yes;"
)
cursor = conn.cursor()
cursor.execute(
    "IF OBJECT_ID('bench') IS NOT NULL DROP TABLE bench;"
    "CREATE TABLE bench (id INT, name VARCHAR(50))"
)
conn.commit()

t0 = time.perf_counter()
for _ in range(N // ROWS_PER_BATCH):
    cursor.execute(SQL, PARAMS)
conn.commit()
ms_time = time.perf_counter() - t0
cursor.close()
conn.close()

# --- pyodbc ---
conn2 = pyodbc.connect(
    "DRIVER={ODBC Driver 18 for SQL Server};"
    "SERVER=localhost;DATABASE=master;UID=sa;PWD=YourPassword;"
    "Encrypt=yes;TrustServerCertificate=yes;"
)
cursor2 = conn2.cursor()
cursor2.execute("TRUNCATE TABLE bench")
conn2.commit()

t0 = time.perf_counter()
for _ in range(N // ROWS_PER_BATCH):
    cursor2.execute(SQL, PARAMS)
conn2.commit()
py_time = time.perf_counter() - t0
cursor2.close()
conn2.close()

print(f"mssql-python: {ms_time:.2f}s ({N / ms_time:,.0f} rows/s)")
print(f"pyodbc:       {py_time:.2f}s ({N / py_time:,.0f} rows/s)")