diff --git a/README.md b/README.md
index cafb15b4..98222f83 100644
--- a/README.md
+++ b/README.md
@@ -4,7 +4,7 @@
   </a>
 </p>
 
-# 🦆 Docling
+# Docling
 
 <p align="center">
   <a href="https://trendshift.io/repositories/12132" target="_blank"><img src="https://trendshift.io/api/badge/repositories/12132" alt="DS4SD%2Fdocling | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
@@ -26,7 +26,7 @@ Docling parses documents and exports them to the desired format with ease and sp
 
 ## Features
 
-* 🗂️ Reads popular document formats (PDF, DOCX, PPTX, XLSX, Images, HTML, AsciiDoc & Markdown) and exports to Markdown and JSON
+* 🗂️ Reads popular document formats (PDF, DOCX, PPTX, XLSX, Images, HTML, AsciiDoc & Markdown) and exports to HTML, Markdown and JSON (with embedded and referenced images)
 * 📑 Advanced PDF document understanding including page layout, reading order & table structures
 * 🧩 Unified, expressive [DoclingDocument](https://ds4sd.github.io/docling/concepts/docling_document/) representation format
 * 🤖 Easy integration with 🦙 LlamaIndex & 🦜🔗 LangChain for powerful RAG / QA applications
diff --git a/docling/cli/main.py b/docling/cli/main.py
index 87a93d15..ee18be97 100644
--- a/docling/cli/main.py
+++ b/docling/cli/main.py
@@ -10,6 +10,7 @@
 from typing import Annotated, Dict, Iterable, List, Optional, Type
 
 import typer
+from docling_core.types.doc import ImageRefMode
 from docling_core.utils.file import resolve_source_to_path
 from pydantic import TypeAdapter, ValidationError
 
@@ -87,9 +88,11 @@ def export_documents(
     conv_results: Iterable[ConversionResult],
     output_dir: Path,
     export_json: bool,
+    export_html: bool,
     export_md: bool,
     export_txt: bool,
     export_doctags: bool,
+    image_export_mode: ImageRefMode,
 ):
 
     success_count = 0
@@ -100,33 +103,45 @@ def export_documents(
             success_count += 1
             doc_filename = conv_res.input.file.stem
 
-            # Export Deep Search document JSON format:
+            # Export JSON format:
             if export_json:
                 fname = output_dir / f"{doc_filename}.json"
-                with fname.open("w", encoding="utf8") as fp:
-                    _log.info(f"writing JSON output to {fname}")
-                    fp.write(json.dumps(conv_res.document.export_to_dict()))
+                _log.info(f"writing JSON output to {fname}")
+                conv_res.document.save_as_json(
+                    filename=fname, image_mode=image_export_mode
+                )
+
+            # Export HTML format:
+            if export_html:
+                fname = output_dir / f"{doc_filename}.html"
+                _log.info(f"writing HTML output to {fname}")
+                conv_res.document.save_as_html(
+                    filename=fname, image_mode=image_export_mode
+                )
 
             # Export Text format:
             if export_txt:
                 fname = output_dir / f"{doc_filename}.txt"
-                with fname.open("w", encoding="utf8") as fp:
-                    _log.info(f"writing Text output to {fname}")
-                    fp.write(conv_res.document.export_to_markdown(strict_text=True))
+                _log.info(f"writing TXT output to {fname}")
+                conv_res.document.save_as_markdown(
+                    filename=fname,
+                    strict_text=True,
+                    image_mode=ImageRefMode.PLACEHOLDER,
+                )
 
             # Export Markdown format:
             if export_md:
                 fname = output_dir / f"{doc_filename}.md"
-                with fname.open("w", encoding="utf8") as fp:
-                    _log.info(f"writing Markdown output to {fname}")
-                    fp.write(conv_res.document.export_to_markdown())
+                _log.info(f"writing Markdown output to {fname}")
+                conv_res.document.save_as_markdown(
+                    filename=fname, image_mode=image_export_mode
+                )
 
             # Export Document Tags format:
             if export_doctags:
                 fname = output_dir / f"{doc_filename}.doctags"
-                with fname.open("w", encoding="utf8") as fp:
-                    _log.info(f"writing Doc Tags output to {fname}")
-                    fp.write(conv_res.document.export_to_document_tokens())
+                _log.info(f"writing Doc Tags output to {fname}")
+                conv_res.document.save_as_document_tokens(filename=fname)
 
         else:
             _log.warning(f"Document {conv_res.input.file} failed to convert.")
@@ -161,6 +176,13 @@ def convert(
     to_formats: List[OutputFormat] = typer.Option(
         None, "--to", help="Specify output formats. Defaults to Markdown."
     ),
+    image_export_mode: Annotated[
+        ImageRefMode,
+        typer.Option(
+            ...,
+            help="Image export mode for the document (only in case of JSON, Markdown or HTML). With `placeholder`, only the position of the image is marked in the output. In `embedded` mode, the image is embedded as base64 encoded string. In `referenced` mode, the image is exported in PNG format and referenced from the main exported document.",
+        ),
+    ] = ImageRefMode.EMBEDDED,
     ocr: Annotated[
         bool,
         typer.Option(
@@ -299,6 +321,7 @@ def convert(
             to_formats = [OutputFormat.MARKDOWN]
 
         export_json = OutputFormat.JSON in to_formats
+        export_html = OutputFormat.HTML in to_formats
         export_md = OutputFormat.MARKDOWN in to_formats
         export_txt = OutputFormat.TEXT in to_formats
         export_doctags = OutputFormat.DOCTAGS in to_formats
@@ -330,6 +353,13 @@ def convert(
         )
         pipeline_options.table_structure_options.mode = table_mode
 
+        if image_export_mode != ImageRefMode.PLACEHOLDER:
+            pipeline_options.generate_page_images = True
+            pipeline_options.generate_picture_images = (
+                True  # FIXME: to be deprecated in verson 3
+            )
+            pipeline_options.images_scale = 2
+
         if artifacts_path is not None:
             pipeline_options.artifacts_path = artifacts_path
 
@@ -364,9 +394,11 @@ def convert(
             conv_results,
             output_dir=output,
             export_json=export_json,
+            export_html=export_html,
             export_md=export_md,
             export_txt=export_txt,
             export_doctags=export_doctags,
+            image_export_mode=image_export_mode,
         )
 
         end_time = time.time() - start_time
diff --git a/docling/datamodel/base_models.py b/docling/datamodel/base_models.py
index 55a19ac3..b71c0f97 100644
--- a/docling/datamodel/base_models.py
+++ b/docling/datamodel/base_models.py
@@ -41,6 +41,7 @@ class InputFormat(str, Enum):
 class OutputFormat(str, Enum):
     MARKDOWN = "md"
     JSON = "json"
+    HTML = "html"
     TEXT = "text"
     DOCTAGS = "doctags"
 
diff --git a/docs/index.md b/docs/index.md
index 3ae3ceb6..7b741728 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -18,7 +18,7 @@ Docling parses documents and exports them to the desired format with ease and sp
 
 ## Features
 
-* 🗂️ Reads popular document formats (PDF, DOCX, PPTX, XLSX, Images, HTML, AsciiDoc & Markdown) and exports to Markdown and JSON
+* 🗂️ Reads popular document formats (PDF, DOCX, PPTX, XLSX, Images, HTML, AsciiDoc & Markdown) and exports to HTML, Markdown and JSON (with embedded and referenced images)
 * 📑 Advanced PDF document understanding incl. page layout, reading order & table structures
 * 🧩 Unified, expressive [DoclingDocument](./concepts/docling_document.md) representation format
 * 🤖 Easy integration with 🦙 LlamaIndex & 🦜🔗 LangChain for powerful RAG / QA applications
diff --git a/mkdocs.yml b/mkdocs.yml
index 731e2ee6..f118edbd 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -53,7 +53,7 @@ theme:
     - toc.follow
 nav:
   - Home:
-    - "🦆 Docling": index.md
+    - "Docling": index.md
     - Installation: installation.md
     - Usage: usage.md
     - CLI: cli.md
diff --git a/poetry.lock b/poetry.lock
index d2a3876d..becf1b33 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -13,87 +13,87 @@ files = [
 
 [[package]]
 name = "aiohttp"
-version = "3.11.9"
+version = "3.11.10"
 description = "Async http client/server framework (asyncio)"
 optional = false
 python-versions = ">=3.9"
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 ]
 
 [package.dependencies]
@@ -136,24 +136,24 @@ files = [
 
 [[package]]
 name = "anyio"
-version = "4.6.2.post1"
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 description = "High level compatibility layer for multiple asynchronous event loop implementations"
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 [[package]]
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 ]
 
 [package.dependencies]
@@ -6894,39 +6798,39 @@ test = ["argcomplete (>=3.0.3)", "mypy (>=1.7.0)", "pre-commit", "pytest (>=7.0,
 
 [[package]]
 name = "transformers"
-version = "4.46.3"
+version = "4.47.0"
 description = "State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow"
 optional = false
-python-versions = ">=3.8.0"
+python-versions = ">=3.9.0"
 files = [
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 ]
 
 [package.dependencies]
 filelock = "*"
-huggingface-hub = ">=0.23.2,<1.0"
+huggingface-hub = ">=0.24.0,<1.0"
 numpy = ">=1.17"
 packaging = ">=20.0"
 pyyaml = ">=5.1"
 regex = "!=2019.12.17"
 requests = "*"
 safetensors = ">=0.4.1"
-tokenizers = ">=0.20,<0.21"
+tokenizers = ">=0.21,<0.22"
 tqdm = ">=4.27"
 
 [package.extras]
 accelerate = ["accelerate (>=0.26.0)"]
 agents = ["Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.26.0)", "datasets (!=2.5.0)", "diffusers", "opencv-python", "sentencepiece (>=0.1.91,!=0.1.92)", "torch"]
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 audio = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
 benchmark = ["optimum-benchmark (>=0.3.0)"]
 codecarbon = ["codecarbon (==1.2.0)"]
 deepspeed = ["accelerate (>=0.26.0)", "deepspeed (>=0.9.3)"]
 deepspeed-testing = ["GitPython (<3.1.19)", "accelerate (>=0.26.0)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "deepspeed (>=0.9.3)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "nltk (<=3.8.1)", "optuna", "parameterized", "protobuf", "psutil", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "timeout-decorator"]
-dev = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.26.0)", "av (==9.2.0)", "beautifulsoup4", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "flax (>=0.4.1,<=0.7.0)", "fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1,<0.14.0)", "libcst", "librosa", "nltk (<=3.8.1)", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rich", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "scipy (<1.13.0)", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timeout-decorator", "timm (<=0.9.16)", "tokenizers (>=0.20,<0.21)", "torch", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"]
-dev-tensorflow = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "isort (>=5.5.4)", "kenlm", "keras-nlp (>=0.3.1,<0.14.0)", "libcst", "librosa", "nltk (<=3.8.1)", "onnxconverter-common", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "rich", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timeout-decorator", "tokenizers (>=0.20,<0.21)", "urllib3 (<2.0.0)"]
-dev-torch = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.26.0)", "beautifulsoup4", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "kenlm", "libcst", "librosa", "nltk (<=3.8.1)", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rich", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "timeout-decorator", "timm (<=0.9.16)", "tokenizers (>=0.20,<0.21)", "torch", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"]
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+dev-tensorflow = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "isort (>=5.5.4)", "kenlm", "keras-nlp (>=0.3.1,<0.14.0)", "libcst", "librosa", "nltk (<=3.8.1)", "onnxconverter-common", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "rich", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timeout-decorator", "tokenizers (>=0.21,<0.22)", "urllib3 (<2.0.0)"]
+dev-torch = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.26.0)", "beautifulsoup4", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "kenlm", "libcst", "librosa", "nltk (<=3.8.1)", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rich", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "timeout-decorator", "timm (<=1.0.11)", "tokenizers (>=0.21,<0.22)", "torch", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"]
 flax = ["flax (>=0.4.1,<=0.7.0)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "optax (>=0.0.8,<=0.1.4)", "scipy (<1.13.0)"]
 flax-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
 ftfy = ["ftfy"]
@@ -6952,12 +6856,12 @@ tf = ["keras-nlp (>=0.3.1,<0.14.0)", "onnxconverter-common", "tensorflow (>2.9,<
 tf-cpu = ["keras (>2.9,<2.16)", "keras-nlp (>=0.3.1,<0.14.0)", "onnxconverter-common", "tensorflow-cpu (>2.9,<2.16)", "tensorflow-probability (<0.24)", "tensorflow-text (<2.16)", "tf2onnx"]
 tf-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
 tiktoken = ["blobfile", "tiktoken"]
-timm = ["timm (<=0.9.16)"]
-tokenizers = ["tokenizers (>=0.20,<0.21)"]
+timm = ["timm (<=1.0.11)"]
+tokenizers = ["tokenizers (>=0.21,<0.22)"]
 torch = ["accelerate (>=0.26.0)", "torch"]
 torch-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"]
 torch-vision = ["Pillow (>=10.0.1,<=15.0)", "torchvision"]
-torchhub = ["filelock", "huggingface-hub (>=0.23.2,<1.0)", "importlib-metadata", "numpy (>=1.17)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.20,<0.21)", "torch", "tqdm (>=4.27)"]
+torchhub = ["filelock", "huggingface-hub (>=0.24.0,<1.0)", "importlib-metadata", "numpy (>=1.17)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.21,<0.22)", "torch", "tqdm (>=4.27)"]
 video = ["av (==9.2.0)"]
 vision = ["Pillow (>=10.0.1,<=15.0)"]
 
@@ -7657,4 +7561,4 @@ tesserocr = ["tesserocr"]
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.9"
-content-hash = "9937d92a9800a7064976f0e1f797c5da648e635c7b331904ad302dacef961ecc"
+content-hash = "5320329d9899ce8577ab91f634df8568f97ab3a9d6d27c06ceba4cffca255533"
diff --git a/pyproject.toml b/pyproject.toml
index 672a3487..8d1a8dcf 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -25,8 +25,8 @@ packages = [{include = "docling"}]
 # actual dependencies:
 ######################
 python = "^3.9"
+docling-core = "^2.7.1"
 pydantic = "^2.0.0"
-docling-core = "^2.7.0"
 docling-ibm-models = "^2.0.6"
 deepsearch-glm = "^0.26.1"
 filetype = "^1.2.0"