diff --git a/HISTORY.md b/HISTORY.md
index d325001698..25d1357573 100644
--- a/HISTORY.md
+++ b/HISTORY.md
@@ -1,3 +1,7 @@
+# 0.47.1
+
+`setprogress!` is now a re-export of `AbstractMCMC.setprogress!`, so `Turing.setprogress!(false)` keeps working and there is a single progress logging switch instead of two. The internal `Turing.PROGRESS` flag is gone, its state lives in `AbstractMCMC.PROGRESS`.
+
 # 0.47.0
 
 ## Breaking changes
diff --git a/Project.toml b/Project.toml
index c113c5bbb9..b73fdf98bd 100644
--- a/Project.toml
+++ b/Project.toml
@@ -1,6 +1,6 @@
 name = "Turing"
 uuid = "fce5fe82-541a-59a6-adf8-730c64b5f9a0"
-version = "0.47.0"
+version = "0.47.1"
 
 [deps]
 ADTypes = "47edcb42-4c32-4615-8424-f2b9edc5f35b"
diff --git a/docs/src/api.md b/docs/src/api.md
index 1342014ae6..6d6a59505d 100644
--- a/docs/src/api.md
+++ b/docs/src/api.md
@@ -146,9 +146,7 @@ See the [AD guide](https://turinglang.org/docs/tutorials/docs-10-using-turing-au
 
 ### Debugging
 
-```@docs
-setprogress!
-```
+`setprogress!` is re-exported from AbstractMCMC. See [`AbstractMCMC.setprogress!`](@extref).
 
 ### Distributions
 
diff --git a/src/Turing.jl b/src/Turing.jl
index 45c6459e7f..7fbddf2140 100644
--- a/src/Turing.jl
+++ b/src/Turing.jl
@@ -14,6 +14,7 @@ using LogDensityProblems: LogDensityProblems
 using StatsAPI: StatsAPI
 using StatsBase: StatsBase
 using AbstractMCMC
+using AbstractMCMC: setprogress!
 using FlexiChains
 
 using Printf: Printf
@@ -24,21 +25,6 @@ using ADTypes: ADTypes, AutoForwardDiff, AutoReverseDiff, AutoMooncake, AutoEnzy
 
 const DEFAULT_ADTYPE = ADTypes.AutoForwardDiff()
 
-const PROGRESS = Ref(true)
-
-# TODO: remove `PROGRESS` and this function in favour of `AbstractMCMC.PROGRESS`
-"""
-    setprogress!(progress::Bool)
-
-Enable progress logging in Turing if `progress` is `true`, and disable it otherwise.
-"""
-function setprogress!(progress::Bool)
-    @info "[Turing]: progress logging is $(progress ? "enabled" : "disabled") globally"
-    PROGRESS[] = progress
-    AbstractMCMC.setprogress!(progress; silent=true)
-    return progress
-end
-
 # Random probability measures.
 include("stdlib/distributions.jl")
 include("stdlib/RandomMeasures.jl")
@@ -141,7 +127,7 @@ export
     AutoReverseDiff,
     AutoMooncake,
     AutoEnzyme,
-    # Debugging - Turing
+    # Progress logging - re-exported from AbstractMCMC
     setprogress!,
     # Distributions
     Flat,
diff --git a/src/mcmc/Inference.jl b/src/mcmc/Inference.jl
index 5d5cf28669..094f63f032 100644
--- a/src/mcmc/Inference.jl
+++ b/src/mcmc/Inference.jl
@@ -18,7 +18,7 @@ using DynamicPPL:
 using Distributions, Libtask, Bijectors
 using FlexiChains: FlexiChains, VNChain
 using LinearAlgebra
-using ..Turing: PROGRESS, Turing
+using ..Turing: Turing
 using StatsFuns: logsumexp
 using Random: AbstractRNG
 using AbstractMCMC: AbstractModel, AbstractSampler
diff --git a/src/mcmc/hmc.jl b/src/mcmc/hmc.jl
index 3e7a28945c..a990cadf89 100644
--- a/src/mcmc/hmc.jl
+++ b/src/mcmc/hmc.jl
@@ -91,7 +91,7 @@ function AbstractMCMC.sample(
     chain_type=DEFAULT_CHAIN_TYPE,
     initial_params=Turing.Inference.init_strategy(sampler),
     initial_state=nothing,
-    progress=PROGRESS[],
+    progress=AbstractMCMC.PROGRESS[],
     nadapts=sampler.n_adapts,
     discard_adapt=true,
     discard_initial=-1,
diff --git a/src/mcmc/repeat_sampler.jl b/src/mcmc/repeat_sampler.jl
index 6f97321da7..3b63c8c1b4 100644
--- a/src/mcmc/repeat_sampler.jl
+++ b/src/mcmc/repeat_sampler.jl
@@ -116,7 +116,7 @@ function AbstractMCMC.sample(
     check_model=true,
     initial_params=Turing.Inference.init_strategy(sampler),
     chain_type=DEFAULT_CHAIN_TYPE,
-    progress=PROGRESS[],
+    progress=AbstractMCMC.PROGRESS[],
     verbose=true,
     kwargs...,
 )
@@ -146,7 +146,7 @@ function AbstractMCMC.sample(
     check_model=true,
     initial_params=fill(Turing.Inference.init_strategy(sampler), n_chains),
     chain_type=DEFAULT_CHAIN_TYPE,
-    progress=PROGRESS[],
+    progress=AbstractMCMC.PROGRESS[],
     kwargs...,
 )
     check_model && Turing._check_model(model, sampler)
diff --git a/src/variational/Variational.jl b/src/variational/Variational.jl
index 0ab9560231..f6ae823235 100644
--- a/src/variational/Variational.jl
+++ b/src/variational/Variational.jl
@@ -18,7 +18,8 @@ using DynamicPPL: DynamicPPL, LogDensityFunction
 using LinearAlgebra
 using LogDensityProblems: LogDensityProblems
 using Random
-using ..Turing: DEFAULT_ADTYPE, PROGRESS
+using ..Turing: DEFAULT_ADTYPE
+import AbstractMCMC
 
 export vi,
     q_locationscale,
@@ -347,7 +348,7 @@ Base.rand(res::VIResult, sz::Integer...) = Base.rand(Random.default_rng(), res,
         ),
         unconstrained::Bool=requires_unconstrained_space(algorithm),
         fix_transforms::Bool=false,
-        show_progress::Bool = Turing.PROGRESS[],
+        show_progress::Bool = AbstractMCMC.PROGRESS[],
         kwargs...
     )
 
@@ -391,7 +392,7 @@ function vi(
     ),
     unconstrained::Bool=requires_unconstrained_space(algorithm),
     fix_transforms::Bool=false,
-    show_progress::Bool=PROGRESS[],
+    show_progress::Bool=AbstractMCMC.PROGRESS[],
     kwargs...,
 )
     transform_strategy = unconstrained ? DynamicPPL.LinkAll() : DynamicPPL.UnlinkAll()
diff --git a/test/variational/vi.jl b/test/variational/vi.jl
index a8bdcc079b..d692653424 100644
--- a/test/variational/vi.jl
+++ b/test/variational/vi.jl
@@ -49,7 +49,9 @@ using Turing.Variational
 
     @testset "default interface" begin
         for q0 in [q_meanfield_gaussian, q_fullrank_gaussian]
-            result = vi(gdemo_default, q0, 100; show_progress=Turing.PROGRESS[], adtype)
+            result = vi(
+                gdemo_default, q0, 100; show_progress=AbstractMCMC.PROGRESS[], adtype
+            )
             @test result isa Turing.Variational.VIResult
             @test rand(result) isa DynamicPPL.VarNamedTuple
             @test rand(result, 2) isa Vector{<:DynamicPPL.VarNamedTuple}
@@ -76,7 +78,7 @@ using Turing.Variational
             q_fullrank_gaussian,
             T;
             algorithm,
-            show_progress=Turing.PROGRESS[],
+            show_progress=AbstractMCMC.PROGRESS[],
         )
         c2 = rand(result, 10)
         @test c2 isa Vector{<:DynamicPPL.VarNamedTuple}
@@ -105,7 +107,7 @@ using Turing.Variational
             q_fullrank_gaussian,
             T;
             algorithm,
-            show_progress=Turing.PROGRESS[],
+            show_progress=AbstractMCMC.PROGRESS[],
         )
 
         N = 1000