diff --git a/integrations/qdrant/CHANGELOG.md b/integrations/qdrant/CHANGELOG.md
index fcece2b193..8d7dfcee3e 100644
--- a/integrations/qdrant/CHANGELOG.md
+++ b/integrations/qdrant/CHANGELOG.md
@@ -1,5 +1,11 @@
 # Changelog
 
+## [Unreleased]
+
+### 🧪 Testing
+
+- Replace in-place `Document` dataclass mutations with `dataclasses.replace()` in sparse embedding retriever tests (#3180)
+
 ## [integrations/qdrant-v10.3.0] - 2026-03-23
 
 ### 📚 Documentation
diff --git a/integrations/qdrant/tests/test_sparse_embedding_retriever.py b/integrations/qdrant/tests/test_sparse_embedding_retriever.py
index 6c1a4ff041..3963d5ba4f 100644
--- a/integrations/qdrant/tests/test_sparse_embedding_retriever.py
+++ b/integrations/qdrant/tests/test_sparse_embedding_retriever.py
@@ -1,3 +1,5 @@
+import dataclasses
+
 import pytest
 from haystack.dataclasses import Document, SparseEmbedding
 from haystack.document_stores.types import FilterPolicy
@@ -153,9 +155,9 @@ def test_run(self, filterable_docs: list[Document], generate_sparse_embedding):
         document_store = QdrantDocumentStore(location=":memory:", index="Boi", use_sparse_embeddings=True)
 
         # Add fake sparse embedding to documents
-        for doc in filterable_docs:
-            doc.sparse_embedding = generate_sparse_embedding()
-
+        filterable_docs = [
+            dataclasses.replace(doc, sparse_embedding=generate_sparse_embedding()) for doc in filterable_docs
+        ]
         document_store.write_documents(filterable_docs)
         retriever = QdrantSparseEmbeddingRetriever(document_store=document_store)
         sparse_embedding = SparseEmbedding(indices=[0, 1, 2, 3], values=[0.1, 0.8, 0.05, 0.33])
@@ -173,9 +175,10 @@ def test_run_with_group_by(self, filterable_docs: list[Document], generate_spars
         document_store = QdrantDocumentStore(location=":memory:", index="Boi", use_sparse_embeddings=True)
 
         # Add fake sparse embedding to documents
-        for index, doc in enumerate(filterable_docs):
-            doc.sparse_embedding = generate_sparse_embedding()
-            doc.meta = {"group_field": index // 2}  # So at least two docs have same group each time
+        filterable_docs = [
+            dataclasses.replace(doc, sparse_embedding=generate_sparse_embedding(), meta={"group_field": index // 2})
+            for index, doc in enumerate(filterable_docs)
+        ]  # So at least two docs have same group each time
         document_store.write_documents(filterable_docs)
         retriever = QdrantSparseEmbeddingRetriever(document_store=document_store)
         sparse_embedding = SparseEmbedding(indices=[0, 1, 2, 3], values=[0.1, 0.8, 0.05, 0.33])
@@ -197,9 +200,9 @@ async def test_run_async(self, filterable_docs: list[Document], generate_sparse_
         document_store = QdrantDocumentStore(location=":memory:", index="Boi", use_sparse_embeddings=True)
 
         # Add fake sparse embedding to documents
-        for doc in filterable_docs:
-            doc.sparse_embedding = generate_sparse_embedding()
-
+        filterable_docs = [
+            dataclasses.replace(doc, sparse_embedding=generate_sparse_embedding()) for doc in filterable_docs
+        ]
         await document_store.write_documents_async(filterable_docs)
         retriever = QdrantSparseEmbeddingRetriever(document_store=document_store)
         sparse_embedding = SparseEmbedding(indices=[0, 1, 2, 3], values=[0.1, 0.8, 0.05, 0.33])
@@ -218,9 +221,10 @@ async def test_run_with_group_by_async(self, filterable_docs: list[Document], ge
         document_store = QdrantDocumentStore(location=":memory:", index="Boi", use_sparse_embeddings=True)
 
         # Add fake sparse embedding to documents
-        for index, doc in enumerate(filterable_docs):
-            doc.sparse_embedding = generate_sparse_embedding()
-            doc.meta = {"group_field": index // 2}  # So at least two docs have same group each time
+        filterable_docs = [
+            dataclasses.replace(doc, sparse_embedding=generate_sparse_embedding(), meta={"group_field": index // 2})
+            for index, doc in enumerate(filterable_docs)
+        ]  # So at least two docs have same group each time
         await document_store.write_documents_async(filterable_docs)
         retriever = QdrantSparseEmbeddingRetriever(document_store=document_store)
         sparse_embedding = SparseEmbedding(indices=[0, 1, 2, 3], values=[0.1, 0.8, 0.05, 0.33])