diff --git a/nimbleModel/DESCRIPTION b/nimbleModel/DESCRIPTION
index 12acd75..b3e53fe 100644
--- a/nimbleModel/DESCRIPTION
+++ b/nimbleModel/DESCRIPTION
@@ -42,6 +42,7 @@ Collate:
     modelFunctions.R
     modelValues.R
     model_utils.R
+    nimCopy.R
     nodeRules.R
     opDefs.R
     options.R       
diff --git a/nimbleModel/NAMESPACE b/nimbleModel/NAMESPACE
index 0e99885..e78e6aa 100644
--- a/nimbleModel/NAMESPACE
+++ b/nimbleModel/NAMESPACE
@@ -83,6 +83,7 @@ export(messageIfVerbose)
 export(calc_dmnormAltParams)
 export(calc_dwishAltParams)
 
+export(nimCopy)
 export(nimbleCode)
 export(nimbleModel)
 export(makeInstrList)
diff --git a/nimbleModel/R/copier.R b/nimbleModel/R/copier.R
index ac9f39c..e45a7ad 100644
--- a/nimbleModel/R/copier.R
+++ b/nimbleModel/R/copier.R
@@ -217,13 +217,15 @@ multiCopierMV_nClass <- nCompiler::nClass(
 
 #' @export
 makeMultiCopier <- function(source, nodes,
-                            sourceType = c("model", "modelValues"), ...) {
-  # This will be called from a nimble2 keyword processor
+                            sourceType = c("model", "modelValues"),
+                            logProb = FALSE, logProbOnly = FALSE, model = NULL, ...) {
+  # This is called from setup code made by nimble2 keyword processing (for nimCopy and values).
+  # logProb and logProbOnly are as for nimCopy (see nimCopy.R). For a modelValues source,
+  # `model` is used to find the logProb elements of nodes.
   # The ... is to absorb further arguments that at the time of this writing are not fleshed out.
-  if (is.character(nodes)) {
-    nodes <- nodes |> lapply(\(x) nimbleModel:::varRangeClass$new(x))
-  }
   sourceType <- match.arg(sourceType)
+  if (sourceType == "model") model <- source
+  nodes <- nimCopy_prepareNodes(model, nodes, logProb, logProbOnly)
   multiCopier <-
     switch(sourceType,
       model = multiCopier_nClass$new(),
diff --git a/nimbleModel/R/nimCopy.R b/nimbleModel/R/nimCopy.R
new file mode 100644
index 0000000..67f9f3b
--- /dev/null
+++ b/nimbleModel/R/nimCopy.R
@@ -0,0 +1,199 @@
+# nimCopy: copy values between models and modelValues objects.
+#
+# As in nimble:
+# - "nodes" are really arbitrary indexed variable ranges and are copied as given, not expanded to nodes.
+#   If nodesTo is missing, it defaults to nodes.
+# - logProb = TRUE also copies the logProb elements of the stochastic nodes in nodes
+#   (including nodes only partly in nodes). logProbOnly = TRUE copies only those.
+# - row is the row of `from` if it is a modelValues object. rowTo is the row of `to`
+#   if it is a modelValues object, defaulting to row.
+#
+# A difference from nimble:
+# Finding the logProb elements of nodes needs a model, so with logProb or logProbOnly,
+# and nodes given, one of from and to must be a model.
+# This might necessitate enhancing modelValues to be know about logProb nodes.
+#
+# In the future, there are several efficiency issues that could be revisited:
+#. - Instead of doing a full get for the "to" nodes just to get lengths, calculate these from indices or objects.
+#. - Check on when assignment ends up creating whole object copies or not.
+#.   This may be particularly the case when uncompiled code works with compiled objects.
+#.  - Consider get-and-set for each, rather than get-all and set-all, but preliminary investigation 
+#.   suggested that overhead of large allocation is minor compared to benefits of the latter.
+#
+#' Copy values between models and modelValues objects
+#'
+#' @param from a model or modelValues object to copy from.
+#' @param to a model or modelValues object to copy to.
+#' @param nodes variables or indexed ranges of variables to copy \code{from}, as a character vector or list
+#'   of varRanges. If missing or NULL, all variables are copied.
+#' @param nodesTo variables or indexed ranges of variables to copy \code{to} If missing or NULL,
+#'   the same as \code{nodes}.
+#' @param row the row of \code{from}, if it is a modelValues object.
+#' @param rowTo the row of \code{to}, if it is a modelValues object. Defaults to \code{row}.
+#' @param logProb whether to also copy the logProb elements of the stochastic nodes in
+#'   \code{nodes} (or all logProb variables if \code{nodes} is missing). One can also manually include
+#'  logProb elements in \code{nodes} or \code{nodesTo}. See details.
+#' @param logProbOnly whether to copy only the logProb elements (or variables).
+#'
+#' @return NULL, invisibly.
+#' @export
+nimCopy <- function(from, to, nodes = NULL, nodesTo = NULL, row = NA, rowTo = NA,
+                    logProb = FALSE, logProbOnly = FALSE) {
+  is_fromMV <- inherits(from, "modelValues")
+  is_toMV <- inherits(to, "modelValues")
+  if (is_fromMV && is.na(row)) stop("nimCopy: row is needed to copy from a modelValues object.")
+  if (is_toMV && is.na(rowTo)) {
+    if (is.na(row)) stop("nimCopy: row or rowTo is needed to copy to a modelValues object.")
+    rowTo <- row
+  }
+  model <- if (!is_fromMV) from else if (!is_toMV) to else NULL
+  if (is.null(nodes)) {
+    fromNodes <- nimCopy_prepareNodes(NULL, nimCopy_allVars(from, logProb, logProbOnly))
+  } else {
+    fromNodes <- nimCopy_prepareNodes(model, nodes, logProb, logProbOnly)
+  }
+  toNodes <- if (is.null(nodesTo)) fromNodes else nimCopy_prepareNodes(model, nodesTo, logProb, logProbOnly)
+
+  vals <- lapply(fromNodes, \(vr) as.numeric(nimCopy_get(from, is_fromMV, vr, row)))
+  vals <- unlist(vals, use.names = FALSE)
+  toLengths <- vapply(toNodes, \(vr) length(nimCopy_get(to, is_toMV, vr, rowTo)), numeric(1))
+  if (sum(toLengths) != length(vals)) {
+    stop("nimCopy: from has ", length(vals), " values to copy, but to has ", sum(toLengths), ".")
+  }
+  offset <- 0
+  for (i in seq_along(toNodes)) {
+    nimCopy_set(to, is_toMV, toNodes[[i]], rowTo, vals[offset + seq_len(toLengths[i])])
+    offset <- offset + toLengths[i]
+  }
+  invisible(NULL)
+}
+
+# The values of varRange vr in a model, or in row `row` of a modelValues object.
+nimCopy_get <- function(source, isMV, vr, row) {
+  var <- vr$varName
+  value <- if (isMV) source[var, row] else source[[var]]
+  eval(vr$toExpr(), envir = structure(list(value), names = var), enclos = baseenv())
+}
+
+# Set the values of varRange vr from v, in flattened (column-major) order.
+nimCopy_set <- function(target, isMV, vr, row, v) {
+  var <- vr$varName
+  expr <- vr$toExpr()
+  if (is.name(expr)) {
+    # A whole variable: keep its dimensions.
+    value <- if (isMV) target[var, row] else target[[var]]
+    value[] <- v
+  } else {
+    env <- new.env(parent = baseenv())
+    env[[var]] <- if (isMV) target[var, row] else target[[var]]
+    env$LocalV_ <- v
+    eval(substitute(E <- LocalV_, list(E = expr)), env)
+    value <- env[[var]]
+  }
+  if (isMV) target[var, row] <- value else target[[var]] <- value
+  invisible(NULL)
+}
+
+# All variables of a model or modelValues object, for nimCopy with nodes missing.
+nimCopy_allVars <- function(source, logProb = FALSE, logProbOnly = FALSE) {
+  vars <- if (inherits(source, "modelValues")) {
+    modelValues_varNames(source)
+  } else {
+    source$getVarNames(includeLogProb = TRUE)
+  }
+  isLP <- startsWith(vars, "logProb_")
+  if (logProbOnly) vars[isLP] else if (logProb) vars else vars[!isLP]
+}
+
+# Make nodes into a list of varRanges, and add the logProb elements of their stochastic nodes
+# (logProb = TRUE) or use only those (logProbOnly = TRUE). Elements of nodes that are already
+# logProb variables are kept with logProb = TRUE and dropped with logProbOnly = TRUE, as in nimble.
+nimCopy_prepareNodes <- function(model, nodes, logProb = FALSE, logProbOnly = FALSE) {
+  if (inherits(nodes, "varRangeClass")) nodes <- list(nodes)
+  if (is.character(nodes)) nodes <- lapply(nodes, \(x) varRangeClass$new(x))
+  if (!(logProb || logProbOnly)) {
+    return(nodes)
+  }
+  if (is.null(model)) {
+    stop(
+      "nimCopy: with logProb = TRUE or logProbOnly = TRUE, from or to must be a model, ",
+      "to find the logProb elements of the nodes."
+    )
+  }
+  isLP <- vapply(nodes, \(vr) startsWith(vr$varName, "logProb_"), logical(1))
+  lpNodes <- list()
+  if (any(!isLP)) {
+    lpNodes <- lapply(logProbNodes(model, nodes[!isLP]), \(x) varRangeClass$new(x))
+  }
+  if (logProbOnly) lpNodes else c(nodes, lpNodes)
+}
+
+# The logProb elements of the stochastic nodes in, or partly in, nodes, as character strings
+# like "logProb_x[2:3, 1]". As in genLogProbExpr, node x[i, 1:2] has logProb element
+# logProb_x[i, 1]: node-internal ranges collapse to their start. So a block of nodes
+# usually gives a block of logProb elements. Other cases give one element per node.
+logProbNodes <- function(model, nodes) {
+  # getNodes takes character node names more generally than varRanges (e.g. a whole variable).
+  if (!is.character(nodes)) nodes <- vapply(nodes, \(vr) safeDeparse(vr$toExpr()), character(1))
+  nodeRanges <- model$getNodes(nodes, stochOnly = TRUE)
+  ans <- lapply(nodeRanges, \(nr) {
+    block <- logProb_block(nr)
+    if (is.null(block)) logProb_per_node(model, nr) else block
+  })
+  unlist(ans, use.names = FALSE)
+}
+
+# The logProb block for a nodeRange whose ranges are each a sequence (or scalar) in one
+# index slot, or NULL otherwise. Internal ranges have constant starts in this case,
+# since a range that depends on the loop indices is not a sequence range.
+logProb_block <- function(nr) {
+  lpName <- makeLogProbName(nr$varName)
+  ranges <- nr$indexRanges
+  if (!length(ranges)) {
+    return(lpName)
+  }
+  isSimple <- vapply(ranges, \(r) inherits(r, c("indexRangeSequenceClass", "indexRangeScalarClass")), logical(1))
+  if (!all(isSimple) || !all(lengths(nr$rangeToIndexSlot) == 1)) {
+    return(NULL)
+  }
+  inds <- character(length(ranges))
+  for (r in seq_along(ranges)) {
+    ir <- ranges[[r]]
+    if (inherits(ir, "indexRangeScalarClass")) {
+      ind <- ir$value
+    } else if (nr$boolExternalIndexRanges[r] && ir$end > ir$start) {
+      ind <- paste0(ir$start, ":", ir$end)
+    } else {
+      ind <- ir$start
+    }
+    inds[nr$rangeToIndexSlot[[r]]] <- ind
+  }
+  paste0(lpName, "[", paste(inds, collapse = ", "), "]")
+}
+
+# The logProb element of each node in a nodeRange, from the declarations' logProb expressions.
+logProb_per_node <- function(model, nr) {
+  instrList <- makeInstrList(model, list(nr))
+  if (is.null(instrList)) {
+    return(NULL)
+  }
+  declInfo <- model$modelDef$declInfo
+  ans <- lapply(instrList$instr_nList, \(instr) {
+    di <- declInfo[[instr$declID]]
+    lpExpr <- di$genLogProbExpr()
+    if (is.null(lpExpr)) {
+      return(NULL)
+    } # not stochastic
+    if (is.name(lpExpr)) {
+      return(as.character(lpExpr))
+    }
+    indexVarNames <- di$declRule$loopIndexingRule$indexVarNames
+    indexExprs <- as.list(lpExpr)[-(1:2)]
+    vapply(seq_len(instr$nNodes), \(k) {
+      idxEnv <- list2env(as.list(structure(set_instr_idx(instr, k), names = indexVarNames)), parent = baseenv())
+      inds <- vapply(indexExprs, \(e) eval(e, idxEnv), numeric(1))
+      paste0(as.character(lpExpr[[2]]), "[", paste(inds, collapse = ", "), "]")
+    }, character(1), USE.NAMES = FALSE)
+  })
+  unlist(ans, use.names = FALSE)
+}
diff --git a/nimbleModel/tests/testthat/test-nimCopy.R b/nimbleModel/tests/testthat/test-nimCopy.R
new file mode 100644
index 0000000..7300330
--- /dev/null
+++ b/nimbleModel/tests/testthat/test-nimCopy.R
@@ -0,0 +1,97 @@
+library(nimbleModel)
+library(testthat)
+library(nCompiler)
+
+# Uncompiled nimCopy and its logProb expansion. Compiled nimCopy (in nimble2 nimbleFunctions)
+# uses the same expansion through makeMultiCopier and is tested in nimble2.
+
+make_nimCopy_model <- function(y = matrix(1:12, 3), mu = 0.2, x = matrix(1:6, 3)) {
+  code <- nimbleCode({
+    mu ~ dnorm(0, sd = 2)
+    for (i in 1:3) {
+      x[i, 1:2] ~ dmnorm(m0[1:2], pr[1:2, 1:2])
+      for (j in 1:4) y[i, j] ~ dnorm(x[i, 1], 1)
+    }
+    w <- mu + 1
+    for (k in 1:2) q[1:2, k] ~ dmnorm(m0[1:2], pr[1:2, 1:2])
+  })
+  m <- nimbleModel(code,
+    data = list(y = y),
+    inits = list(mu = mu, m0 = c(0, 0), pr = diag(2), x = x, q = diag(2))
+  )
+  m$calculate()
+  m
+}
+
+test_that("logProbNodes gives logProb blocks, including for partly covered nodes", {
+  m <- make_nimCopy_model()
+  expect_identical(nimbleModel:::logProbNodes(m, "mu"), "logProb_mu")
+  expect_identical(nimbleModel:::logProbNodes(m, "x"), "logProb_x[1:3, 1]")
+  expect_identical(nimbleModel:::logProbNodes(m, "x[2:3, 1]"), "logProb_x[2:3, 1]") # partly covered
+  expect_identical(nimbleModel:::logProbNodes(m, "q[2, 1:2]"), "logProb_q[1, 1:2]") # internal range first
+  expect_identical(nimbleModel:::logProbNodes(m, "y[1:2, 2:3]"), "logProb_y[1:2, 2:3]")
+  expect_identical(nimbleModel:::logProbNodes(m, "y"), "logProb_y[1:3, 1:4]")
+  expect_identical(nimbleModel:::logProbNodes(m, c("w", "mu")), "logProb_mu") # deterministic w has none
+  expect_length(nimbleModel:::logProbNodes(m, "w"), 0)
+})
+
+test_that("logProbNodes gives one element per node when there is no block", {
+  code <- nimbleCode({
+    for (i in 1:3) z[i, i:(i + 1)] ~ dmnorm(m0[1:2], pr[1:2, 1:2]) # internal range depends on i
+    for (i in 1:3) v[2 * i] ~ dnorm(0, 1)
+  })
+  m <- suppressMessages(nimbleModel(code, inits = list(m0 = c(0, 0), pr = diag(2))))
+  expect_identical(
+    nimbleModel:::logProbNodes(m, "z"),
+    c("logProb_z[1, 1]", "logProb_z[2, 2]", "logProb_z[3, 3]")
+  )
+  expect_identical(nimbleModel:::logProbNodes(m, "v"), c("logProb_v[2]", "logProb_v[4]", "logProb_v[6]"))
+})
+
+test_that("uncompiled nimCopy copies between models and modelValues, with logProb and logProbOnly", {
+  m <- make_nimCopy_model()
+  mv <- modelValues(m)$new()
+  resize(mv, 2)
+
+  # model to modelValues, with logProb
+  nimCopy(m, mv, nodes = c("mu", "x[2:3, 1:2]"), row = 2, logProb = TRUE)
+  expect_equal(mv["mu", 2], 0.2)
+  expect_equal(mv["x", 2], rbind(0, m$x[2:3, ]))
+  expect_equal(mv["logProb_mu", 2], m$logProb_mu)
+  expect_equal(mv["logProb_x", 2], cbind(c(0, m$logProb_x[2:3, 1]), 0))
+  expect_equal(mv["x", 1], matrix(0, 3, 2)) # other row untouched
+
+  # nodes missing: all variables, or only logProb variables
+  mv2 <- modelValues(m)$new()
+  resize(mv2, 1)
+  nimCopy(m, mv2, row = 1, logProbOnly = TRUE)
+  expect_equal(mv2["logProb_y", 1], m$logProb_y)
+  expect_equal(mv2["x", 1], matrix(0, 3, 2))
+  nimCopy(m, mv2, row = 1)
+  expect_equal(mv2["x", 1], m$x)
+  expect_equal(mv2["pr", 1], diag(2))
+
+  # modelValues to model, with nodesTo
+  m3 <- make_nimCopy_model(y = matrix(0, 3, 4), mu = 0, x = matrix(0, 3, 2))
+  nimCopy(mv, m3, nodes = "x[2:3, 1:2]", nodesTo = "x[1:2, 1:2]", row = 2)
+  expect_equal(m3$x, rbind(m$x[2:3, ], 0))
+
+  # model to model, with logProb; a whole variable keeps its dimensions
+  nimCopy(m, m3, nodes = "y", logProb = TRUE)
+  expect_equal(m3$y, m$y)
+  expect_equal(m3$logProb_y, m$logProb_y)
+
+  # modelValues to modelValues needs a model for logProb expansion of nodes, but not with nodes missing
+  expect_error(nimCopy(mv, mv2, nodes = "x", row = 2, rowTo = 1, logProb = TRUE), "must be a model")
+  nimCopy(mv, mv2, row = 2, rowTo = 1, logProb = TRUE)
+  expect_equal(mv2["x", 1], mv["x", 2])
+  expect_equal(mv2["logProb_x", 1], mv["logProb_x", 2])
+
+  # logProb from a modelValues to a model uses the model to find the logProb elements
+  m3$logProb_mu <- 0
+  nimCopy(mv, m3, nodes = "mu", row = 2, logProb = TRUE)
+  expect_equal(m3$logProb_mu, m$logProb_mu)
+
+  expect_error(nimCopy(m, m3, nodes = "x", nodesTo = "mu"), "6 values to copy, but to has 1")
+  expect_error(nimCopy(mv, m3, nodes = "x"), "row is needed")
+})