diff --git a/DESCRIPTION b/DESCRIPTION
index 1fab0614c..25a7bd6d3 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -97,5 +97,6 @@ Authors@R: c(
   person("Vincent", "Runge",       role="ctb"),
   person("Christian", "Wia",       role="ctb"),
   person("Elise", "Maigné",        role="ctb"),
-  person("Vincent", "Rocher",      role="ctb")
+  person("Vincent", "Rocher",      role="ctb"),
+  person("Vijay", "Lulla",         role="ctb")
   )
diff --git a/NEWS.md b/NEWS.md
index be02a0522..f203117ba 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -105,6 +105,8 @@ rowwiseDT(
 
 10. `DT[1, on=NULL]` now works for returning the first row, [#6579](https://github.com/Rdatatable/data.table/issues/6579). Thanks to @Kodiologist for the report and @tdhock for the PR.
 
+11. `tables()` now returns the correct size for data.tables over 2GiB, [#6607](https://github.com/Rdatatable/data.table/issues/6607). Thanks to @vlulla for the report and the PR.
+
 ## NOTES
 
 1. Tests run again when some Suggests packages are missing, [#6411](https://github.com/Rdatatable/data.table/issues/6411). Thanks @aadler for the note and @MichaelChirico for the fix.
diff --git a/R/tables.R b/R/tables.R
index 7662598d8..18729ee03 100644
--- a/R/tables.R
+++ b/R/tables.R
@@ -5,7 +5,7 @@ type_size = function(DT) {
   # for speed and ram efficiency, a lower bound by not descending into character string lengths or list items
   # if a more accurate and higher estimate is needed then user can pass object.size or alternative to mb=
   # in case number of columns is very large (e.g. 1e6 columns) then we use a for() to avoid allocation of sapply()
-  ans = 0L
+  ans = 0.0
   lookup = c("raw"=1L, "integer"=4L, "double"=8L, "complex"=16L)
   for (i in seq_along(DT)) {
     col = DT[[i]]
diff --git a/inst/tests/other.Rraw b/inst/tests/other.Rraw
index 044d82cfa..96f40b071 100644
--- a/inst/tests/other.Rraw
+++ b/inst/tests/other.Rraw
@@ -766,3 +766,10 @@ if (loaded[["nanotime"]]) {
   # respect dec=',' for nanotime, related to #6446, corresponding to tests 2281.*
   test(31, fwrite(data.table(as.nanotime(.POSIXct(0))), dec=',', sep=';'), output="1970-01-01T00:00:00,000000000Z")
 }
+
+# tables() with large environment #6607
+.e <- new.env() ## to not populate the .GlobalEnv
+.e[["DT"]] <- as.data.table(lapply(1:15,function(i) runif(20e6)))
+res <- tables(env=.e)
+test(32, res[, .(NAME,NROW,NCOL,MB)], data.table(NAME="DT",NROW=20000000L,NCOL=15L,MB=2288.0))
+rm(.e, res)