diff --git a/mteb/models/model_implementations/clips_models.py b/mteb/models/model_implementations/clips_models.py
new file mode 100644
index 0000000000..17073d05cd
--- /dev/null
+++ b/mteb/models/model_implementations/clips_models.py
@@ -0,0 +1,97 @@
+from mteb.models.model_meta import (
+    ModelMeta,
+    ScoringFunction,
+)
+from mteb.models.sentence_transformer_wrapper import sentence_transformers_loader
+
+from .e5_models import ME5_TRAINING_DATA, model_prompts
+
+E5_NL_CITATION = """
+@misc{banar2025mtebnle5nlembeddingbenchmark,
+  archiveprefix = {arXiv},
+  author = {Nikolay Banar and Ehsan Lotfi and Jens Van Nooten and Cristina Arhiliuc and Marija Kliocaite and Walter Daelemans},
+  eprint = {2509.12340},
+  primaryclass = {cs.CL},
+  title = {MTEB-NL and E5-NL: Embedding Benchmark and Models for Dutch},
+  url = {https://arxiv.org/abs/2509.12340},
+  year = {2025},
+}
+"""
+
+e5_nl_small = ModelMeta(
+    loader=sentence_transformers_loader,
+    loader_kwargs=dict(
+        model_prompts=model_prompts,
+    ),
+    name="clips/e5-small-trm-nl",
+    languages=["nld-Latn"],
+    open_weights=True,
+    revision="0243664a6c5e12eef854b091eb283e51833c3e9f",
+    release_date="2025-09-23",
+    n_parameters=40_800_000,
+    memory_usage_mb=78,
+    embed_dim=384,
+    license="mit",
+    max_tokens=512,
+    reference="https://huggingface.co/clips/e5-small-trm-nl",
+    similarity_fn_name=ScoringFunction.COSINE,
+    framework=["Sentence Transformers", "PyTorch"],
+    use_instructions=True,
+    public_training_code="https://github.com/ELotfi/e5-nl",
+    public_training_data="https://huggingface.co/collections/clips/beir-nl",
+    training_datasets=ME5_TRAINING_DATA,  # mMARCO-NL, HotpotQA-NL, FEVER-NL, and LLM generated data
+    adapted_from="intfloat/multilingual-e5-small",
+    citation=E5_NL_CITATION,
+)
+
+e5_nl_base = ModelMeta(
+    loader=sentence_transformers_loader,
+    loader_kwargs=dict(
+        model_prompts=model_prompts,
+    ),
+    name="clips/e5-base-trm-nl",
+    languages=["nld-Latn"],
+    open_weights=True,
+    revision="6bd5722f236da48b4b8bcb28cc1fc478f7089956",
+    release_date="2025-09-23",
+    n_parameters=124_400_000,
+    memory_usage_mb=237,
+    embed_dim=768,
+    license="mit",
+    max_tokens=514,
+    reference="https://huggingface.co/clips/e5-base-trm-nl",
+    similarity_fn_name=ScoringFunction.COSINE,
+    framework=["Sentence Transformers", "PyTorch"],
+    use_instructions=True,
+    public_training_code="https://github.com/ELotfi/e5-nl",
+    public_training_data="https://huggingface.co/collections/clips/beir-nl",
+    adapted_from="intfloat/multilingual-e5-base",
+    training_datasets=ME5_TRAINING_DATA,  # mMARCO-NL, HotpotQA-NL, FEVER-NL, and LLM generated data
+    citation=E5_NL_CITATION,
+)
+
+e5_nl_large = ModelMeta(
+    loader=sentence_transformers_loader,
+    loader_kwargs=dict(
+        model_prompts=model_prompts,
+    ),
+    name="clips/e5-large-trm-nl",
+    languages=["nld-Latn"],
+    open_weights=True,
+    revision="683333f86ed9eb3699b5567f0fdabeb958d412b0",
+    release_date="2025-09-23",
+    n_parameters=355_000_000,
+    memory_usage_mb=1355,
+    embed_dim=1024,
+    license="mit",
+    max_tokens=514,
+    reference="https://huggingface.co/clips/e5-large-trm-nl",
+    similarity_fn_name=ScoringFunction.COSINE,
+    framework=["Sentence Transformers", "PyTorch"],
+    use_instructions=True,
+    public_training_code="https://github.com/ELotfi/e5-nl",
+    public_training_data="https://huggingface.co/collections/clips/beir-nl",
+    training_datasets=ME5_TRAINING_DATA,  # mMARCO-NL, HotpotQA-NL, FEVER-NL, and LLM generated data
+    adapted_from="intfloat/multilingual-e5-large",
+    citation=E5_NL_CITATION,
+)