diff --git a/.lightning/workflows/tests.yaml b/.lightning/workflows/tests.yaml
index 3ee3903737..aaacc4bdaf 100644
--- a/.lightning/workflows/tests.yaml
+++ b/.lightning/workflows/tests.yaml
@@ -53,6 +53,11 @@ run: |
 
   pytest -v --durations=100
 
+  if [ "${dependency}" == "" ]; then
+    # Run the tokenizer tests (CPU-only, so excluded above) with the registry fallback for gated repos.
+    RUN_ONLY_CUDA_TESTS=0 LITGPT_TOKENIZER_REGISTRY_FALLBACK=1 timeout 10m pytest tests/test_tokenizer.py -v -s -rs --timeout=100 --durations=50
+  fi
+
   wget https://raw.githubusercontent.com/Lightning-AI/utilities/main/scripts/run_standalone_tests.sh
   PL_RUN_STANDALONE_TESTS=1 bash run_standalone_tests.sh "tests"
 
diff --git a/pyproject.toml b/pyproject.toml
index 56852615ed..df9d1e8856 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -74,6 +74,7 @@ optional-dependencies.extra = [
 ]
 optional-dependencies.test = [
   "einops>=0.7",
+  "litmodels>=0.1.8",
   "protobuf>=4.23.4",
   "pytest>=8.1.1",
   "pytest-benchmark>=5.1",
diff --git a/tests/test_tokenizer.py b/tests/test_tokenizer.py
index c950de6043..ae8f79a121 100644
--- a/tests/test_tokenizer.py
+++ b/tests/test_tokenizer.py
@@ -37,6 +37,35 @@ def _is_hf_skip_error(ex: Exception) -> bool:
     return status in (401, 403, 429)
 
 
+# Teamspace holding the tokenizer mirrors. The mirror name is derived from the HF repo id.
+_TOKENIZER_REGISTRY_TEAMSPACE = "lightning-ai/oss-litgpt"
+
+
+def _download_gated_tokenizer_mirror(repo_id: str, dest: Path) -> Path | None:
+    """Download a gated repo's tokenizer files from the Lightning Model Registry mirror.
+
+    Returns the download directory, or ``None`` if the fallback is disabled or the mirror is
+    unavailable. Enabled with ``LITGPT_TOKENIZER_REGISTRY_FALLBACK=1``.
+    """
+    if os.getenv("LITGPT_TOKENIZER_REGISTRY_FALLBACK", "0") != "1":
+        return None
+    try:
+        from litmodels import download_model
+    except ImportError as ex:
+        print(f"[registry-fallback] {repo_id}: litmodels not available: {ex!r}")
+        return None
+    slug = repo_id.lower().replace("/", "--").replace(".", "-")
+    name = f"{_TOKENIZER_REGISTRY_TEAMSPACE}/{slug}-tokenizer"
+    print(f"[registry-fallback] {repo_id}: trying mirror {name}")
+    try:
+        files = download_model(name, download_dir=str(dest), progress_bar=False)
+    except Exception as ex:
+        print(f"[registry-fallback] {repo_id}: mirror download failed: {ex!r}")
+        return None
+    print(f"[registry-fallback] {repo_id}: downloaded {files}")
+    return dest
+
+
 # @pytest.mark.flaky(reruns=3, rerun_except=["AssertionError", "assert", "TypeError"])
 @pytest.mark.flaky(reruns=3, reruns_delay=120)
 @pytest.mark.parametrize("config", config_module.configs, ids=[c["hf_config"]["name"] for c in config_module.configs])
@@ -47,15 +76,19 @@ def test_tokenizer_against_hf(config, tmp_path):
 
     try:
         # Download only tokenizer/config files (no weights). `snapshot_download` raises a typed
-        # `GatedRepoError`, so we skip gated repos cleanly instead of retrying for minutes on
+        # `GatedRepoError`, so we handle gated repos cleanly instead of retrying for minutes on
         # fork PRs that have no HF_TOKEN.
         cache_dir = snapshot_download(repo_id, allow_patterns=list(_TOKENIZER_FILES), token=os.getenv("HF_TOKEN"))
         theirs = AutoTokenizer.from_pretrained(repo_id, token=os.getenv("HF_TOKEN"))
     except Exception as ex:
-        # TODO: Resolve with Lightning Registry model for gated HF tokenizer tests.
         if not _is_hf_skip_error(ex):
             raise
-        pytest.skip(f"{repo_id} is gated on Hugging Face and cannot be loaded without HF_TOKEN.")
+        # No HF_TOKEN: fall back to the registry mirror and load the tokenizer from local files.
+        # Skip if the fallback is disabled or there is no mirror for this repo.
+        cache_dir = _download_gated_tokenizer_mirror(repo_id, tmp_path / "registry")
+        if cache_dir is None:
+            pytest.skip(f"{repo_id} is gated on Hugging Face and has no registry mirror.")
+        theirs = AutoTokenizer.from_pretrained(cache_dir)
 
     # litgpt's Tokenizer infers BOS from the directory name (e.g. `SmolLM2-*-Instruct`, `Llama-3*`),
     # so copy the files into a model-named dir, not the cache's commit-hash snapshot path.