diff --git a/NAMESPACE b/NAMESPACE
index 7dd831f..5d88f48 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -15,6 +15,7 @@ S3method(textmodel_lsa,tokens)
 S3method(textmodel_word2vec,tokens)
 export(analogy)
 export(as.textmodel_doc2vec)
+export(perplexity)
 export(probability)
 export(similarity)
 export(textmodel_doc2vec)
diff --git a/R/as.doc2vec.R b/R/as.doc2vec.R
index 0f1dbcd..95281fa 100644
--- a/R/as.doc2vec.R
+++ b/R/as.doc2vec.R
@@ -65,6 +65,7 @@ as.textmodel_doc2vec.dfm <- function(x, model = NULL, normalize = FALSE,
     result <- list(
         "values" = list("word" = wov, "doc" = dov),
         "dim" = model$dim,
+        "tolower" = model$tolower,
         "concatenator" = conc, 
         "docvars" = x@docvars,
         "normalize" = normalize,
diff --git a/R/lsa.R b/R/lsa.R
index 7fa096e..651f1f1 100644
--- a/R/lsa.R
+++ b/R/lsa.R
@@ -90,15 +90,16 @@ textmodel_lsa.dfm <- function(x, dim = 50L, min_count = 5L,
         rownames(wov) <- featnames(x)
     }
     result <- list(
-        values = list(word = wov),
-        dim = dim,
-        frequency = featfreq(x),
-        engine = engine,
-        weight = weight,
-        min_count = min_count,
-        concatenator = meta(x, field = "concatenator", type = "object"),
-        call = try(match.call(sys.function(-1), call = sys.call(-1)), silent = TRUE),
-        version = utils::packageVersion("wordvector")
+        "values" = list(word = wov),
+        "dim" = dim,
+        "frequency" = featfreq(x),
+        "engine" = engine,
+        "weight" = weight,
+        "min_count" = min_count,
+        "tolower" = tolower,
+        "concatenator" = meta(x, field = "concatenator", type = "object"),
+        "call" = try(match.call(sys.function(-1), call = sys.call(-1)), silent = TRUE),
+        "version" = utils::packageVersion("wordvector")
     )
     class(result) <- c("textmodel_lsa", "textmodel_wordvector")
     return(result)
diff --git a/R/utils.R b/R/utils.R
index 51d78d8..eb71075 100644
--- a/R/utils.R
+++ b/R/utils.R
@@ -95,9 +95,9 @@ similarity <- function(x, targets, layer = c("words", "documents"),
 #' Compute probability of words
 #'
 #' Compute the probability of words given other words.
-#' @param x a `textmodel_wordvector` object fitted with `normalize = FALSE`.
-#' @param targets words for which probability is computed.
-#' @param layer the layer based on which probability is computed.
+#' @param x a trained `textmodel_wordvector` object.
+#' @param targets words for which probabilities are computed.
+#' @param layer the layer based on which probabilities are computed.
 #' @param mode specify the type of resulting object.
 #' @return a matrix of words or documents sorted in descending order by the probability 
 #'   scores when `mode = "character"`; a matrix of the probability scores when `mode = "numeric"`.
@@ -164,6 +164,31 @@ probability <- function(x, targets, layer = c("words", "documents"),
     return(res)
 }
 
+#' Compute perplexity of a model
+#'
+#' Compute the perplexity of a trained word2vec model with data.
+#' @param x a trained `textmodel_wordvector` object.
+#' @param targets words for which probabilities are computed.
+#' @param data a [quanteda::tokens] or [quanteda::dfm]; the probabilities of words are 
+#'    tested against occurrences of words in it.
+#' @export
+#' @keywords internal
+perplexity <- function(x, targets, data) {
+    x <- upgrade_pre06(x)
+    
+    if (!is.character(targets))
+        stop("targets must be a character vector")
+    
+    if (!is.tokens(data) && !is.dfm(data))
+        stop("data must be a tokens or dfm")
+    data <- dfm(data, remove_padding = TRUE, tolower = x$tolower)
+    
+    p <- probability(x, targets, mode = "numeric")
+    pred <- dfm_match(dfm_weight(data, "prop"), rownames(p)) %*% p
+    tri <- Matrix::mat2triplet(dfm_match(data, colnames(pred)))
+    exp(-sum(tri$x * log(pred[cbind(tri$i, tri$j)])) / sum(tri$x))
+}
+
 get_threads <- function() {
     
     # respect other settings
@@ -194,6 +219,9 @@ upgrade_pre06 <- function(x) {
     if (is.numeric(x$type)) {
         x$type <- c("cbow", "sg")[x$type]
     }
+    if (is.null(x$tolower)) {
+        x$tolower <- TRUE
+    }
     return(x)
 }
 
diff --git a/R/word2vec.R b/R/word2vec.R
index f51fac7..a906aac 100644
--- a/R/word2vec.R
+++ b/R/word2vec.R
@@ -160,6 +160,7 @@ wordvector <- function(x, dim = 50, type = c("cbow", "sg", "dm", "dbow"),
     
     result$type <- type
     result$min_count <- min_count
+    result$tolower <- tolower
     result$concatenator <- meta(x, field = "concatenator", type = "object")
     if (include_data) # NOTE: consider removing
         result$data <- y
diff --git a/man/perplexity.Rd b/man/perplexity.Rd
new file mode 100644
index 0000000..bc26ff8
--- /dev/null
+++ b/man/perplexity.Rd
@@ -0,0 +1,20 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/utils.R
+\name{perplexity}
+\alias{perplexity}
+\title{Compute perplexity of a model}
+\usage{
+perplexity(x, targets, data)
+}
+\arguments{
+\item{x}{a trained \code{textmodel_wordvector} object.}
+
+\item{targets}{words for which probabilities are computed.}
+
+\item{data}{a \link[quanteda:tokens]{quanteda::tokens} or \link[quanteda:dfm]{quanteda::dfm}; the probabilities of words are
+tested against occurrences of words in it.}
+}
+\description{
+Compute the perplexity of a trained word2vec model with data.
+}
+\keyword{internal}
diff --git a/man/probability.Rd b/man/probability.Rd
index 8b193a2..c101f43 100644
--- a/man/probability.Rd
+++ b/man/probability.Rd
@@ -12,11 +12,11 @@ probability(
 )
 }
 \arguments{
-\item{x}{a \code{textmodel_wordvector} object fitted with \code{normalize = FALSE}.}
+\item{x}{a trained \code{textmodel_wordvector} object.}
 
-\item{targets}{words for which probability is computed.}
+\item{targets}{words for which probabilities are computed.}
 
-\item{layer}{the layer based on which probability is computed.}
+\item{layer}{the layer based on which probabilities are computed.}
 
 \item{mode}{specify the type of resulting object.}
 }
diff --git a/tests/misc/test_small.R b/tests/misc/test_small.R
index a6a019e..ac78227 100644
--- a/tests/misc/test_small.R
+++ b/tests/misc/test_small.R
@@ -30,28 +30,36 @@ wdv$weights["america",]
 wdv2$weights["america",]
 wdv3$weights["america",]
 
-#dov <- textmodel_doc2vec(toks, dim = 50, type = "cbow", min_count = 5, verbose = TRUE, iter = 10)
-dov <- textmodel_doc2vec(toks, dim = 50, type = "skip-gram", min_count = 5, verbose = TRUE, iter = 10)
+dov <- textmodel_doc2vec(toks, dim = 100, type = "dm", min_count = 5, verbose = TRUE, iter = 10)
+dov2 <- textmodel_doc2vec(toks, dim = 100, type = "dm", min_count = 5, verbose = TRUE, iter = 20)
 
-similarity(dov, analogy(~ washington - america + france)) %>% 
-    head()
+sim <- proxyC::simil(
+    dov$values$doc,
+    dov$values$doc["3555430",, drop = FALSE]
+)
+tail(sort(s <- rowSums(sim)))
 
-probability(dov, c("good")) %>% 
-    head()
+sim2 <- proxyC::simil(
+    dov2$values$doc,
+    dov2$values$doc["3555430",, drop = FALSE]
+)
+tail(sort(s2 <- rowSums(sim2)))
+
+identical(s, s2)
+cor(s, s2)
 
 sim <- proxyC::simil(
-    dov$values$doc,
-    dov$values$doc["4263794",, drop = FALSE]
+    dov2$values$doc,
+    dov2$values$doc["4263794",, drop = FALSE]
 )
 sim <- proxyC::simil(
-    dov$values$doc,
-    dov$values$doc["3016236",, drop = FALSE]
+    dov2$values$doc,
+    dov2$values$doc["3016236",, drop = FALSE]
 )
 sim <- proxyC::simil(
-    dov$values$doc,
-    dov$values$doc["3555430",, drop = FALSE]
+    dov2$values$doc,
+    dov2$values$doc["3555430",, drop = FALSE]
 )
-
 tail(sort(s <- rowSums(sim)))
 print(tail(toks[order(s)]), max_ntoken = -1)
 
diff --git a/tests/testthat/test-as.doc2vec.R b/tests/testthat/test-as.doc2vec.R
index b3f55d9..9be3904 100644
--- a/tests/testthat/test-as.doc2vec.R
+++ b/tests/testthat/test-as.doc2vec.R
@@ -20,7 +20,7 @@ test_that("textmodel_doc2vec works", {
     expect_false(dov1$normalize)
     expect_equal(
         names(dov1),
-        c("values", "dim", "concatenator", "docvars", "normalize", "call", "version")
+        c("values", "dim", "tolower", "concatenator", "docvars", "normalize", "call", "version")
     )
     expect_equal(
         dim(dov1$values$word), c(5363L, 50L)
diff --git a/tests/testthat/test-doc2vec.R b/tests/testthat/test-doc2vec.R
index 0de2f4b..8c2f3ea 100644
--- a/tests/testthat/test-doc2vec.R
+++ b/tests/testthat/test-doc2vec.R
@@ -21,7 +21,8 @@ test_that("textmodel_doc2vec works", {
     expect_equal(
         names(dov1),
         c("values", "weights", "type", "dim", "frequency", "window",  "iter", "alpha", 
-          "use_ns", "ns_size", "sample", "normalize",  "min_count", "concatenator", "docvars", "call", "version")
+          "use_ns", "ns_size", "sample", "normalize",  "min_count", "tolower",
+          "concatenator", "docvars", "call", "version")
     )
     expect_equal(
         dim(dov1$values$word), c(5363L, 50L)
@@ -64,7 +65,8 @@ test_that("textmodel_doc2vec works", {
     expect_equal(
         names(dov2),
         c("values", "weights", "type", "dim", "frequency", "window",  "iter", "alpha", 
-          "use_ns", "ns_size", "sample", "normalize",  "min_count", "concatenator", "docvars", "call", "version")
+          "use_ns", "ns_size", "sample", "normalize",  "min_count", "tolower",
+          "concatenator", "docvars", "call", "version")
     )
     expect_null(
         dov2$values$word
diff --git a/tests/testthat/test-lsa.R b/tests/testthat/test-lsa.R
index d356cd3..8c49121 100644
--- a/tests/testthat/test-lsa.R
+++ b/tests/testthat/test-lsa.R
@@ -49,7 +49,8 @@ test_that("word2vec words", {
     )
     expect_equal(
         names(dov),
-        c("values", "dim", "concatenator", "docvars", "normalize", "call", "version")
+        c("values", "dim", "tolower", "concatenator", "docvars", "normalize", 
+          "call", "version")
     )
     
     # docvector with model
@@ -78,7 +79,7 @@ test_that("word2vec words", {
     )
     expect_equal(
         names(dov),
-        c("values", "dim", "concatenator", "docvars", "normalize", "call", "version")
+        c("values", "dim", "tolower", "concatenator", "docvars", "normalize", "call", "version")
     )
     
     # docvector with grouped data
@@ -94,7 +95,7 @@ test_that("word2vec words", {
     )
     expect_equal(
         names(dov_gp),
-        c("values", "dim", "concatenator", "docvars", "normalize", "call", "version")
+        c("values", "dim", "tolower", "concatenator", "docvars", "normalize", "call", "version")
     )
 })
 
diff --git a/tests/testthat/test-utils.R b/tests/testthat/test-utils.R
index c5b5027..c03698c 100644
--- a/tests/testthat/test-utils.R
+++ b/tests/testthat/test-utils.R
@@ -430,3 +430,37 @@ test_that("old arguments still works", {
     )
     
 })
+
+test_that("perplexity works", {
+    
+    # infrequent words
+    word1 <- c("good", "nice", "excellent", "positive", "fortunate", "correct", "superior", 
+              "bad", "nasty", "poor", "negative", "unfortunate",  "wrong", "inferior")
+    suppressWarnings(
+        ppl1 <- perplexity(wov, word1, dfmt)
+    )
+    expect_gt(ppl1, 3.0)
+    
+    # frequent words
+    word2 <- c("america", "us", "people", "government", "state", "nation", "world", "peace", "public")
+    suppressWarnings(
+        ppl2 <- perplexity(wov, word2, dfmt)
+    )
+    expect_lt(ppl2, ppl1)
+    
+    # tokens_object
+    suppressWarnings(
+        ppl3 <- perplexity(wov, word2, toks)
+    )
+    expect_equal(ppl3, ppl2)
+    
+    expect_error(
+        perplexity(wov, c("good" = 1, "bad" = -1), dfmt),
+        "targets must be a character vector"
+    )
+    
+    expect_error(
+        perplexity(wov, word2, list),
+        "data must be a tokens or dfm"
+    )
+})
diff --git a/tests/testthat/test-word2vec.R b/tests/testthat/test-word2vec.R
index f757cbc..97ea3b7 100644
--- a/tests/testthat/test-word2vec.R
+++ b/tests/testthat/test-word2vec.R
@@ -49,6 +49,9 @@ test_that("textmodel_word2vec works", {
         featfreq(dfm_trim(dfm(toks), 2)),
         wov1$frequency
     )
+    expect_true(
+        wov1$tolower
+    )
     
     expect_output(
         print(wov1),
@@ -113,6 +116,9 @@ test_that("textmodel_word2vec works", {
         featfreq(dfm_trim(dfm(toks), 2)),
         wov2$frequency
     )
+    expect_true(
+        wov2$tolower
+    )
     
     expect_output(
         print(wov2),