diff --git a/integration-tests/clean_cache_and_download.py b/integration-tests/clean_cache_and_download.py
new file mode 100644
index 00000000..5b75d668
--- /dev/null
+++ b/integration-tests/clean_cache_and_download.py
@@ -0,0 +1,158 @@
+import huggingface_hub
+import argparse
+import shutil
+import time
+
+REQUIRED_MODELS = {
+    "bigscience/bloom-560m": "main",
+    "TinyLlama/TinyLlama-1.1B-Chat-v1.0": "main",
+    "abhinavkulkarni/codellama-CodeLlama-7b-Python-hf-w4-g128-awq": "main",
+    "tiiuae/falcon-7b": "main",
+    "TechxGenus/gemma-2b-GPTQ": "main",
+    "google/gemma-2b": "main",
+    "openai-community/gpt2": "main",
+    "turboderp/Llama-3-8B-Instruct-exl2": "2.5bpw",
+    "huggingface/llama-7b-gptq": "main",
+    "neuralmagic/llama-2-7b-chat-marlin": "main",
+    "huggingface/llama-7b": "main",
+    "FasterDecoding/medusa-vicuna-7b-v1.3": "refs/pr/1",
+    "mistralai/Mistral-7B-Instruct-v0.1": "main",
+    "OpenAssistant/oasst-sft-1-pythia-12b": "main",
+    "stabilityai/stablelm-tuned-alpha-3b": "main",
+    "google/paligemma-3b-pt-224": "main",
+    "microsoft/phi-2": "main",
+    "Qwen/Qwen1.5-0.5B": "main",
+    "bigcode/starcoder": "main",
+    "Narsil/starcoder-gptq": "main",
+    "bigcode/starcoder2-3b": "main",
+    "HuggingFaceM4/idefics-9b-instruct": "main",
+    "HuggingFaceM4/idefics2-8b": "main",
+    "llava-hf/llava-v1.6-mistral-7b-hf": "main",
+    "state-spaces/mamba-130m": "main",
+    "mosaicml/mpt-7b": "main",
+    "bigscience/mt0-base": "main",
+    "google/flan-t5-xxl": "main",
+}
+
+
+def cleanup_cache(token: str):
+    # Retrieve the size per model for all models used in the CI.
+    size_per_model = {}
+    extension_per_model = {}
+    for model_id, revision in REQUIRED_MODELS.items():
+        model_size = 0
+        all_files = huggingface_hub.list_repo_files(
+            model_id,
+            repo_type="model",
+            revision=revision,
+            token=token,
+        )
+
+        extension = None
+        if any(".safetensors" in filename for filename in all_files):
+            extension = ".safetensors"
+        elif any(".pt" in filename for filename in all_files):
+            extension = ".pt"
+        elif any(".bin" in filename for filename in all_files):
+            extension = ".bin"
+
+        extension_per_model[model_id] = extension
+
+        for filename in all_files:
+            if filename.endswith(extension):
+                file_url = huggingface_hub.hf_hub_url(
+                    model_id, filename, revision=revision
+                )
+                file_metadata = huggingface_hub.get_hf_file_metadata(
+                    file_url, token=token
+                )
+                model_size += file_metadata.size * 1e-9  # in GB
+
+        size_per_model[model_id] = model_size
+
+    total_required_size = sum(size_per_model.values())
+    print(f"Total required disk: {total_required_size:.2f} GB")
+
+    cached_dir = huggingface_hub.scan_cache_dir()
+
+    cache_size_per_model = {}
+    cached_required_size_per_model = {}
+    cached_shas_per_model = {}
+
+    # Retrieve the SHAs and model ids of other non-necessary models in the cache.
+    for repo in cached_dir.repos:
+        if repo.repo_id in REQUIRED_MODELS:
+            cached_required_size_per_model[repo.repo_id] = (
+                repo.size_on_disk * 1e-9
+            )  # in GB
+        elif repo.repo_type == "model":
+            cache_size_per_model[repo.repo_id] = repo.size_on_disk * 1e-9  # in GB
+
+            shas = []
+            for rev in repo.revisions:
+                shas.append(rev.commit_hash)
+            cached_shas_per_model[repo.repo_id] = shas
+
+    total_required_cached_size = sum(cached_required_size_per_model.values())
+    total_other_cached_size = sum(cache_size_per_model.values())
+    total_non_cached_required_size = total_required_size - total_required_cached_size
+
+    print(
+        f"Total HF cached models size: {total_other_cached_size + total_required_cached_size:.2f} GB"
+    )
+    print(
+        f"Total non-necessary HF cached models size: {total_other_cached_size:.2f} GB"
+    )
+
+    free_memory = shutil.disk_usage("/data").free * 1e-9
+    print(f"Free memory: {free_memory:.2f} GB")
+
+    if free_memory + total_other_cached_size < total_non_cached_required_size * 1.05:
+        raise ValueError(
+            "Not enough space on device to execute the complete CI, please clean up the CI machine"
+        )
+
+    while free_memory < total_non_cached_required_size * 1.05:
+        if len(cache_size_per_model) == 0:
+            raise ValueError("This should not happen.")
+
+        largest_model_id = max(cache_size_per_model, key=cache_size_per_model.get)
+
+        print("Removing", largest_model_id)
+        for sha in cached_shas_per_model[largest_model_id]:
+            huggingface_hub.scan_cache_dir().delete_revisions(sha).execute()
+
+        del cache_size_per_model[largest_model_id]
+
+        free_memory = shutil.disk_usage("/data").free * 1e-9
+
+    return extension_per_model
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="Cache cleaner")
+    parser.add_argument(
+        "--token", help="Hugging Face Hub token.", required=True, type=str
+    )
+    args = parser.parse_args()
+
+    start = time.time()
+    extension_per_model = cleanup_cache(args.token)
+    end = time.time()
+
+    print(f"Cache cleanup done in {end - start:.2f} s")
+
+    print("Downloading required models")
+    start = time.time()
+    for model_id, revision in REQUIRED_MODELS.items():
+        print(f"Downloading {model_id}'s *{extension_per_model[model_id]}...")
+        huggingface_hub.snapshot_download(
+            model_id,
+            repo_type="model",
+            revision=revision,
+            token=args.token,
+            allow_patterns=f"*{extension_per_model[model_id]}",
+        )
+    end = time.time()
+
+    print(f"Models download done in {end - start:.2f} s")