diff --git a/poetry.lock b/poetry.lock
index 8cbd28643a..a7bb9267f0 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -121,13 +121,13 @@ tests-no-zope = ["cloudpickle", "coverage[toml] (>=5.0.2)", "hypothesis", "mypy"
 
 [[package]]
 name = "autoray"
-version = "0.6.9"
+version = "0.6.11"
 description = "Abstract your array operations."
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "autoray-0.6.11-py3-none-any.whl", hash = "sha256:93c96ee6f8436e71a7887fa6b782458f0f7a027de94b61b87ffa540971d9fdf9"},
+    {file = "autoray-0.6.11.tar.gz", hash = "sha256:23e6dc013913de318952580cfbf054920ebd5eacd060fc48edebb678307b4b0d"},
 ]
 
 [package.extras]
@@ -136,13 +136,13 @@ tests = ["coverage", "numpy", "pytest", "pytest-cov"]
 
 [[package]]
 name = "babel"
-version = "2.14.0"
+version = "2.15.0"
 description = "Internationalization utilities"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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-    {file = "Babel-2.14.0.tar.gz", hash = "sha256:6919867db036398ba21eb5c7a0f6b28ab8cbc3ae7a73a44ebe34ae74a4e7d363"},
+    {file = "Babel-2.15.0-py3-none-any.whl", hash = "sha256:08706bdad8d0a3413266ab61bd6c34d0c28d6e1e7badf40a2cebe67644e2e1fb"},
+    {file = "babel-2.15.0.tar.gz", hash = "sha256:8daf0e265d05768bc6c7a314cf1321e9a123afc328cc635c18622a2f30a04413"},
 ]
 
 [package.extras]
@@ -678,63 +678,63 @@ test = ["altair", "baytune", "chocolate", "dask", "distributed", "kahypar", "mat
 
 [[package]]
 name = "coverage"
-version = "7.5.0"
+version = "7.5.1"
 description = "Code coverage measurement for Python"
 optional = false
 python-versions = ">=3.8"
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@@ -852,24 +852,24 @@ numpy = ">=1.21,<2.0"
 
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 python-versions = "*"
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 python-versions = "*"
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+version = "2.4.0.post1"
 description = "cuTensorNet - a component of NVIDIA cuQuantum SDK"
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 python-versions = "*"
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+version = "2.4.0.post1"
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 [package.extras]
-protobuf = ["grpcio-tools (>=1.62.2)"]
+protobuf = ["grpcio-tools (>=1.63.0)"]
 
 [[package]]
 name = "grpcio-status"
@@ -1915,13 +1907,13 @@ testing = ["Django", "attrs", "colorama", "docopt", "pytest (<7.0.0)"]
 
 [[package]]
 name = "jinja2"
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 description = "A very fast and expressive template engine."
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.dependencies]
@@ -1932,13 +1924,13 @@ i18n = ["Babel (>=2.7)"]
 
 [[package]]
 name = "joblib"
-version = "1.4.0"
+version = "1.4.2"
 description = "Lightweight pipelining with Python functions"
 optional = false
 python-versions = ">=3.8"
 files = [
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 [[package]]
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@@ -3256,13 +3245,13 @@ xmp = ["defusedxml"]
 
 [[package]]
 name = "platformdirs"
-version = "4.2.1"
+version = "4.2.2"
 description = "A small Python package for determining appropriate platform-specific dirs, e.g. a `user data dir`."
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.extras]
@@ -3535,17 +3524,16 @@ email = ["email-validator (>=1.0.3)"]
 
 [[package]]
 name = "pygments"
-version = "2.17.2"
+version = "2.18.0"
 description = "Pygments is a syntax highlighting package written in Python."
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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 [package.extras]
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 [[package]]
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@@ -4057,7 +4045,7 @@ scipy = "^1.10.1"
 type = "git"
 url = "https://github.com/qiboteam/qibojit.git"
 reference = "HEAD"
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+resolved_reference = "de78b0d879ee2d64b0fe28a5d7aaeb4b7f6e84d7"
 
 [[package]]
 name = "qibotn"
@@ -4078,18 +4066,18 @@ cuda = ["cupy-cuda11x (>=11.6.0,<12.0.0)", "cuquantum-python-cu11 (>=23.3.0,<24.
 [package.source]
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 url = "https://github.com/qiboteam/qibotn.git"
-reference = "HEAD"
-resolved_reference = "6814fdbe19df19678299f9a4f662410256762ac1"
+reference = "list_backends"
+resolved_reference = "217a6338bce0120159fc77648ec38d8d894197c2"
 
 [[package]]
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-version = "1.8.0"
+version = "1.8.1"
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 python-versions = ">=3.8"
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@@ -4770,17 +4758,18 @@ files = [
 
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 name = "tenacity"
-version = "8.2.3"
+version = "8.3.0"
 description = "Retry code until it succeeds"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "tenacity-8.2.3-py3-none-any.whl", hash = "sha256:ce510e327a630c9e1beaf17d42e6ffacc88185044ad85cf74c0a8887c6a0f88c"},
-    {file = "tenacity-8.2.3.tar.gz", hash = "sha256:5398ef0d78e63f40007c1fb4c0bff96e1911394d2fa8d194f77619c05ff6cc8a"},
+    {file = "tenacity-8.3.0-py3-none-any.whl", hash = "sha256:3649f6443dbc0d9b01b9d8020a9c4ec7a1ff5f6f3c6c8a036ef371f573fe9185"},
+    {file = "tenacity-8.3.0.tar.gz", hash = "sha256:953d4e6ad24357bceffbc9707bc74349aca9d245f68eb65419cf0c249a1949a2"},
 ]
 
 [package.extras]
-doc = ["reno", "sphinx", "tornado (>=4.5)"]
+doc = ["reno", "sphinx"]
+test = ["pytest", "tornado (>=4.5)", "typeguard"]
 
 [[package]]
 name = "tensorboard"
@@ -4876,32 +4865,35 @@ and-cuda = ["nvidia-cublas-cu12 (==12.3.4.1)", "nvidia-cuda-cupti-cu12 (==12.3.1
 
 [[package]]
 name = "tensorflow-io-gcs-filesystem"
-version = "0.36.0"
+version = "0.37.0"
 description = "TensorFlow IO"
 optional = false
-python-versions = ">=3.7, <3.12"
-files = [
-    {file = "tensorflow_io_gcs_filesystem-0.36.0-cp310-cp310-macosx_10_14_x86_64.whl", hash = "sha256:702c6df62b38095ff613c433546d9424d4f33902a5ab26b00fd26457e27a99fa"},
-    {file = "tensorflow_io_gcs_filesystem-0.36.0-cp310-cp310-macosx_12_0_arm64.whl", hash = "sha256:e9b8aaca2789af356c42afda0f52380f82e5abb2f3c0b85087833fcfe03875d8"},
-    {file = "tensorflow_io_gcs_filesystem-0.36.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c477aed96864ceae77d7051c3b687f28813aba7320fc5dd552164fad6ec8d1a1"},
-    {file = "tensorflow_io_gcs_filesystem-0.36.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:be1ff92559dfa23048b01179a1827081947583f5c6f9986ccac471df8a29322a"},
-    {file = "tensorflow_io_gcs_filesystem-0.36.0-cp311-cp311-macosx_10_14_x86_64.whl", hash = "sha256:72c3ca4b8c0d8dbdd970699d05a100107cf200317ad8e6a8373e2c37225cd552"},
-    {file = "tensorflow_io_gcs_filesystem-0.36.0-cp311-cp311-macosx_12_0_arm64.whl", hash = "sha256:848e8e89a0f49258c7782189c938d8d1162d989da1a80c79f95c7af3ef6006c8"},
-    {file = "tensorflow_io_gcs_filesystem-0.36.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4d72db1ab03edb65fa1e98d06e504ccbc64282d38ab3589afb6db66dc448d1c1"},
-    {file = "tensorflow_io_gcs_filesystem-0.36.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1bd4d946b5fa23220daa473a80e511a5fb27493d7e49d17dff0bb43bb0a31f32"},
-    {file = "tensorflow_io_gcs_filesystem-0.36.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:fa346fd1dd9f57848b73874007440504f060fadd689fa1cc29cc49817d0eeaf3"},
-    {file = "tensorflow_io_gcs_filesystem-0.36.0-cp39-cp39-macosx_10_14_x86_64.whl", hash = "sha256:0a4437824424a4423cf86162cb8b21b1bec24698194332748b50bb952e62ab9f"},
-    {file = "tensorflow_io_gcs_filesystem-0.36.0-cp39-cp39-macosx_12_0_arm64.whl", hash = "sha256:31806bd7ac2db789161bc720747de22947063265561a4c17be54698fd9780b03"},
-    {file = "tensorflow_io_gcs_filesystem-0.36.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:fc0e57976c1aa035af6281f0330cfb8dd50eee2f63412ecc84d60ff5075d29b7"},
-    {file = "tensorflow_io_gcs_filesystem-0.36.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e97ff5c280eb10f699098ae21057be2b146d39e8a906cd5db91f2ea6c34e47d0"},
+python-versions = "<3.12,>=3.7"
+files = [
+    {file = "tensorflow_io_gcs_filesystem-0.37.0-cp310-cp310-macosx_10_14_x86_64.whl", hash = "sha256:82cc4d8e26fb143fc814ac8ab95fede83363a315f5b62f8ae68312f1aca1cc6e"},
+    {file = "tensorflow_io_gcs_filesystem-0.37.0-cp310-cp310-macosx_12_0_arm64.whl", hash = "sha256:677d6d7c84a94a3b27ea5d16633ea09adadef09c2630480e8e94209558828b02"},
+    {file = "tensorflow_io_gcs_filesystem-0.37.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8e5d1ac4d2010e8cdf259918ba1500c942b51b7ed2e549f55b404c1fb52f695d"},
+    {file = "tensorflow_io_gcs_filesystem-0.37.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0e2901bc4a91158fa0a10d37594c8a5efb1445dd5a041b1b5b90f782a5d1b15e"},
+    {file = "tensorflow_io_gcs_filesystem-0.37.0-cp311-cp311-macosx_10_14_x86_64.whl", hash = "sha256:eab6e4c1daf7ddbfef608cd8e2102861021678dfb3f6a7fb3f613db9d6992919"},
+    {file = "tensorflow_io_gcs_filesystem-0.37.0-cp311-cp311-macosx_12_0_arm64.whl", hash = "sha256:4ec3c0d0a9d3676a2e74198e3dff66d74c7c34f974257f2176236d0703b31a0e"},
+    {file = "tensorflow_io_gcs_filesystem-0.37.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:af0f79400656bb88bf326d2b8e63aef49c07a0ce8c14c3e2589a62e765d8c21f"},
+    {file = "tensorflow_io_gcs_filesystem-0.37.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:13bc337f2c2db63a39c81c8fd0ececc0c3d5fcf4ce229dfed0b0085a23dd60e9"},
+    {file = "tensorflow_io_gcs_filesystem-0.37.0-cp312-cp312-macosx_10_14_x86_64.whl", hash = "sha256:57e7af9c81e79bf8fb552985dc8972ac90437d34bd4c1c9019a92a07eb12bc98"},
+    {file = "tensorflow_io_gcs_filesystem-0.37.0-cp312-cp312-macosx_12_0_arm64.whl", hash = "sha256:48a8e7aec651bea8db410f6426c6446a56d16a5ab32201a70d8d684c113137b7"},
+    {file = "tensorflow_io_gcs_filesystem-0.37.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:71ccf64a137efcb2be2627225b4e48110cbf34da39b23c5cc688fe803f2510f1"},
+    {file = "tensorflow_io_gcs_filesystem-0.37.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:03d5598b8007551f4e1391bf85a83a1865e3fa0789beef15a200efaa06a23fb5"},
+    {file = "tensorflow_io_gcs_filesystem-0.37.0-cp39-cp39-macosx_10_14_x86_64.whl", hash = "sha256:8d3ad5f30b6dbe09baefdb80e9aa7ff3869c772928b865f8ffc8402be7675a43"},
+    {file = "tensorflow_io_gcs_filesystem-0.37.0-cp39-cp39-macosx_12_0_arm64.whl", hash = "sha256:95bb229e968fca943806c6ac04e81dc4966fc4a36ab83efaa061a4ecb3ea5e85"},
+    {file = "tensorflow_io_gcs_filesystem-0.37.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8385f4fe447812bd8e2e11ef523cf02765319100e5d9e4a9b5a876d4440c900c"},
+    {file = "tensorflow_io_gcs_filesystem-0.37.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:500ec871a8d59cf78992b7fd4750d86ea3d35e231fb0bea7a7eabcf73abfceeb"},
 ]
 
 [package.extras]
-tensorflow = ["tensorflow (>=2.15.0,<2.16.0)"]
-tensorflow-aarch64 = ["tensorflow-aarch64 (>=2.15.0,<2.16.0)"]
-tensorflow-cpu = ["tensorflow-cpu (>=2.15.0,<2.16.0)"]
-tensorflow-gpu = ["tensorflow-gpu (>=2.15.0,<2.16.0)"]
-tensorflow-rocm = ["tensorflow-rocm (>=2.15.0,<2.16.0)"]
+tensorflow = ["tensorflow (>=2.16.0,<2.17.0)"]
+tensorflow-aarch64 = ["tensorflow-aarch64 (>=2.16.0,<2.17.0)"]
+tensorflow-cpu = ["tensorflow-cpu (>=2.16.0,<2.17.0)"]
+tensorflow-gpu = ["tensorflow-gpu (>=2.16.0,<2.17.0)"]
+tensorflow-rocm = ["tensorflow-rocm (>=2.16.0,<2.17.0)"]
 
 [[package]]
 name = "termcolor"
@@ -4970,13 +4962,13 @@ files = [
 
 [[package]]
 name = "tomlkit"
-version = "0.12.4"
+version = "0.12.5"
 description = "Style preserving TOML library"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "tomlkit-0.12.4-py3-none-any.whl", hash = "sha256:5cd82d48a3dd89dee1f9d64420aa20ae65cfbd00668d6f094d7578a78efbb77b"},
-    {file = "tomlkit-0.12.4.tar.gz", hash = "sha256:7ca1cfc12232806517a8515047ba66a19369e71edf2439d0f5824f91032b6cc3"},
+    {file = "tomlkit-0.12.5-py3-none-any.whl", hash = "sha256:af914f5a9c59ed9d0762c7b64d3b5d5df007448eb9cd2edc8a46b1eafead172f"},
+    {file = "tomlkit-0.12.5.tar.gz", hash = "sha256:eef34fba39834d4d6b73c9ba7f3e4d1c417a4e56f89a7e96e090dd0d24b8fb3c"},
 ]
 
 [[package]]
@@ -5066,13 +5058,13 @@ files = [
 
 [[package]]
 name = "tqdm"
-version = "4.66.2"
+version = "4.66.4"
 description = "Fast, Extensible Progress Meter"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "tqdm-4.66.2-py3-none-any.whl", hash = "sha256:1ee4f8a893eb9bef51c6e35730cebf234d5d0b6bd112b0271e10ed7c24a02bd9"},
-    {file = "tqdm-4.66.2.tar.gz", hash = "sha256:6cd52cdf0fef0e0f543299cfc96fec90d7b8a7e88745f411ec33eb44d5ed3531"},
+    {file = "tqdm-4.66.4-py3-none-any.whl", hash = "sha256:b75ca56b413b030bc3f00af51fd2c1a1a5eac6a0c1cca83cbb37a5c52abce644"},
+    {file = "tqdm-4.66.4.tar.gz", hash = "sha256:e4d936c9de8727928f3be6079590e97d9abfe8d39a590be678eb5919ffc186bb"},
 ]
 
 [package.dependencies]
@@ -5377,4 +5369,4 @@ torch = ["torch"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9,<3.13"
-content-hash = "c96177091d8cbe08f1791d4962a7b638d185e2cd35bff80e8afc7a239e4ae6b3"
+content-hash = "7c184ed22c205d782c9d0656cd22ab6eefd03d4b59965cdab0c1869d04fb810e"
diff --git a/pyproject.toml b/pyproject.toml
index 529231632d..09df68f500 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -65,12 +65,12 @@ cirq = "^1.1.0"
 ply = "^3.11"
 scikit-learn = "^1.2.1"
 pytest-cov = "^4.0.0"
-pylint = "^3.1.0"
+pylint = "3.1.0"
 matplotlib = "^3.7.0"
 tensorflow = { version = "^2.16.1", markers = "sys_platform == 'linux'" }
 torch = "^2.1.1"
 qibojit = { git = "https://github.com/qiboteam/qibojit.git" }
-qibotn = { git = "https://github.com/qiboteam/qibotn.git" }
+qibotn = { git = "https://github.com/qiboteam/qibotn.git", branch = "list_backends" }
 stim = "^1.12.0"
 
 [tool.poe.tasks]
@@ -89,7 +89,7 @@ optional = true
 cupy-cuda11x = "^12.0.0"
 cuquantum-python-cu11 = "^23.3.0"
 qibojit = { git = "https://github.com/qiboteam/qibojit.git" }
-qibotn = { git = "https://github.com/qiboteam/qibotn.git" }
+qibotn = { git = "https://github.com/qiboteam/qibotn.git", branch = "list_backends" }
 
 [tool.poetry.group.cuda12]
 optional = true
@@ -98,7 +98,7 @@ optional = true
 cupy-cuda12x = "^12.0.0"
 cuquantum-python-cu12 = "^23.3.0"
 qibojit = { git = "https://github.com/qiboteam/qibojit.git" }
-qibotn = { git = "https://github.com/qiboteam/qibotn.git" }
+qibotn = { git = "https://github.com/qiboteam/qibotn.git", branch = "list_backends" }
 
 [tool.poetry.extras]
 tensorflow = ["tensorflow"]
diff --git a/src/qibo/__init__.py b/src/qibo/__init__.py
index b895e37b0f..bcd912f1cc 100644
--- a/src/qibo/__init__.py
+++ b/src/qibo/__init__.py
@@ -14,10 +14,12 @@
     solvers,
 )
 from qibo.backends import (
+    construct_backend,
     get_backend,
     get_device,
     get_precision,
     get_threads,
+    list_available_backends,
     matrices,
     set_backend,
     set_device,
diff --git a/src/qibo/backends/__init__.py b/src/qibo/backends/__init__.py
index 3a34c6077e..a3076a5de4 100644
--- a/src/qibo/backends/__init__.py
+++ b/src/qibo/backends/__init__.py
@@ -1,7 +1,9 @@
 import os
+from importlib import import_module
 
 import numpy as np
 
+from qibo.backends.abstract import Backend
 from qibo.backends.clifford import CliffordBackend
 from qibo.backends.npmatrices import NumpyMatrices
 from qibo.backends.numpy import NumpyBackend
@@ -9,66 +11,51 @@
 from qibo.backends.tensorflow import TensorflowBackend
 from qibo.config import log, raise_error
 
-
-def construct_backend(backend, **kwargs):
-    if backend == "qibojit":
-        from qibojit.backends import CupyBackend, CuQuantumBackend, NumbaBackend
-
-        platform = kwargs.get("platform")
-        if platform == "cupy":  # pragma: no cover
-            return CupyBackend()
-        elif platform == "cuquantum":  # pragma: no cover
-            return CuQuantumBackend()
-        elif platform == "numba":
-            return NumbaBackend()
-        else:  # pragma: no cover
+QIBO_NATIVE_BACKENDS = ("numpy", "tensorflow", "pytorch")
+QIBO_NON_NATIVE_BACKENDS = ("qibojit", "qibolab", "qibo-cloud-backends", "qibotn")
+
+
+class MetaBackend:
+    """Meta-backend class which takes care of loading the qibo backends."""
+
+    @staticmethod
+    def load(backend: str, **kwargs) -> Backend:
+        """Loads the native qibo backend.
+
+        Args:
+            backend (str): Name of the backend to load.
+            kwargs (dict): Additional arguments for the qibo backend.
+        Returns:
+            qibo.backends.abstract.Backend: The loaded backend.
+        """
+
+        if backend == "numpy":
+            return NumpyBackend()
+        elif backend == "tensorflow":
+            return TensorflowBackend()
+        elif backend == "pytorch":
+            return PyTorchBackend()
+        elif backend == "clifford":
+            engine = kwargs.pop("platform", None)
+            kwargs["engine"] = engine
+            return CliffordBackend(**kwargs)
+        else:
+            raise_error(
+                ValueError,
+                f"Backend {backend} is not available. The native qibo backends are {QIBO_NATIVE_BACKENDS}.",
+            )
+
+    def list_available(self) -> dict:
+        """Lists all the available native qibo backends."""
+        available_backends = {}
+        for backend in QIBO_NATIVE_BACKENDS:
             try:
-                return CupyBackend()
-            except (ModuleNotFoundError, ImportError):
-                return NumbaBackend()
-
-    elif backend == "tensorflow":
-        return TensorflowBackend()
-
-    elif backend == "pytorch":
-        return PyTorchBackend()
-
-    elif backend == "numpy":
-        return NumpyBackend()
-
-    elif backend == "qibolab":  # pragma: no cover
-        from qibolab.backends import QibolabBackend  # pylint: disable=E0401
-
-        return QibolabBackend(**kwargs)
-
-    elif backend == "qibotn":  # pragma: no cover
-
-        platform = kwargs.get("platform")
-        if platform == "cutensornet":  # pragma: no cover
-            from qibotn.backends.cutensornet import CuTensorNet  # pylint: disable=E0401
-
-            return CuTensorNet(kwargs["runcard"])
-        elif platform == "qutensornet":  # pragma: no cover
-            from qibotn.backends.quimb import QuimbBackend  # pylint: disable=E0401
-
-            return QuimbBackend(kwargs["runcard"])
-
-    elif backend == "clifford":
-        return CliffordBackend(kwargs["platform"])
-    elif backend == "qibo-client":  # pragma: no cover
-        from qibo_cloud_backends.qibo_client import (  # pylint: disable=E0401
-            QiboClientBackend,
-        )
-
-        return QiboClientBackend(**kwargs)
-    elif backend == "qiskit":  # pragma: no cover
-        from qibo_cloud_backends.qiskit_client import (  # pylint: disable=E0401
-            QiskitClientBackend,
-        )
-
-        return QiskitClientBackend(**kwargs)
-    else:  # pragma: no cover
-        raise_error(ValueError, f"Backend {backend} is not available.")
+                MetaBackend.load(backend)
+                available = True
+            except:  # pragma: no cover
+                available = False
+            available_backends[backend] = available
+        return available_backends
 
 
 class GlobalBackend(NumpyBackend):
@@ -203,6 +190,40 @@ def _check_backend(backend):
     return backend
 
 
+def list_available_backends() -> dict:
+    """Lists all the backends that are available."""
+    available_backends = MetaBackend().list_available()
+    for backend in QIBO_NON_NATIVE_BACKENDS:
+        try:
+            module = import_module(backend.replace("-", "_"))
+            available = getattr(module, "MetaBackend")().list_available()
+        except:
+            available = False
+        available_backends.update({backend: available})
+    return available_backends
+
+
+def construct_backend(backend, **kwargs) -> Backend:
+    """Construct a generic native or non-native qibo backend.
+    Args:
+        backend (str): Name of the backend to load.
+        kwargs (dict): Additional arguments for constructing the backend.
+    Returns:
+        qibo.backends.abstract.Backend: The loaded backend.
+
+    """
+    if backend in QIBO_NATIVE_BACKENDS + ("clifford",):
+        return MetaBackend.load(backend, **kwargs)
+    elif backend in QIBO_NON_NATIVE_BACKENDS:
+        module = import_module(backend.replace("-", "_"))
+        return getattr(module, "MetaBackend").load(**kwargs)
+    else:
+        raise_error(
+            ValueError,
+            f"Backend {backend} is not available. To check which backends are installed use `qibo.list_available_backends()`.",
+        )
+
+
 def _check_backend_and_local_state(seed, backend):
     if (
         seed is not None
diff --git a/tests/test_backends.py b/tests/test_backends.py
index 61ed409f49..876e931b2f 100644
--- a/tests/test_backends.py
+++ b/tests/test_backends.py
@@ -1,7 +1,10 @@
+import platform
+
 import numpy as np
 import pytest
 
-from qibo import gates
+from qibo import construct_backend, gates, list_available_backends, set_backend
+from qibo.backends import MetaBackend
 
 ####################### Test `matrix` #######################
 GATES = [
@@ -122,3 +125,33 @@ def test_plus_density_matrix(backend):
     matrix = backend.plus_density_matrix(4)
     target_matrix = np.ones((16, 16)) / 16
     backend.assert_allclose(matrix, target_matrix)
+
+
+def test_set_backend_error():
+    with pytest.raises(ValueError):
+        set_backend("non-existing-backend")
+
+
+def test_metabackend_load_error():
+    with pytest.raises(ValueError):
+        MetaBackend.load("non-existing-backend")
+
+
+def test_construct_backend(backend):
+    assert isinstance(
+        construct_backend(backend.name, platform=backend.platform), backend.__class__
+    )
+
+
+def test_list_available_backends():
+    tensorflow = False if platform.system() == "Windows" else True
+    available_backends = {
+        "numpy": True,
+        "tensorflow": tensorflow,
+        "pytorch": True,
+        "qibojit": {"numba": True, "cupy": False, "cuquantum": False},
+        "qibolab": False,
+        "qibo-cloud-backends": False,
+        "qibotn": {"cutensornet": False, "qutensornet": True},
+    }
+    assert available_backends == list_available_backends()