Best way to smooth normals. I know of one method, not sure if it's very memory efficient.

The informations you gave us are very sparse.

1. Which criterion do you use to qualify what good, better, and best is in this context?

2. What does "smooth normals" mean? An average of normals as it occurs when computing a vertex normal from the normals of surrounding faces? Or an interpolation of normals as it occur to fill gaps between samples? Or realigning existing normals to appear smoothly arranged? Or something else?

3. Which method is the one you know?

4. How is normal "smoothing" meant to be memory efficient / inefficient?

// set all normals to zero
for each vertex normal (n)
  n = 0,0,0

// add in each face normal to each vertex normal
for each face
  fn = calculate face normal 
  for each vertex normal in face (vn)
     vn += fn

// normalize normals
for each vertex normal (n)
  normalize(n)

// set all normals to zero
for each vertex normal (n)
  n = 0,0,0

// add in each face normal to each vertex normal
for each face
  fn = calculate face normal 
  for each vertex normal in face (vn)
     vn += fn

// normalize normals
for each vertex normal (n)
  normalize(n)

This algorithm calculates a vertex normal by averaging normals of surrounding faces. While there is nothing inherently wrong with it, one usually wants to consider a weight so that the face normals have differently rated influence. A typical weights are the face areas, another is the angle of the face at the vertex of interest.