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Guide
Parse
v1
Features

Multimodal Parsing

Multimodal parsing screenshots each page and sends it to a vendor multimodal model for markdown extraction, optionally using your own provider or Azure key.

You can use a Vendor multimodal model to handle document extraction. This is more expensive than regular parsing but can get better results for some documents.

Supported models are models are here.

When using this mode, LlamaParse’s regular parsing is bypassed and instead the following process is used:

  • A screenshot of every page of your document is taken
  • Each page screenshot is sent to the multimodal with instruction to extract as markdown
  • The resulting markdown of each page is consolidated into the final result.


To use the multimodal mode, set use_vendor_multimodal_model to True. You can then select which model to use ny setting vendor_multimodal_model_name to the model you want to target (eg: anthropic-sonnet-3.5).

parser = LlamaParse(
use_vendor_multimodal_model=True,
vendor_multimodal_model_name="anthropic-sonnet-3.5"
)


When using To use the multimodal mode, you can supply your own vendor key to parse the document. If you choose to do so LlamaParse will only charge you 1 credit (0.3c) per page.

Using your own API key will incur some price from your model provider, and could led to fail page/document if you do not have high usage limits.

To use your own API key set the parameter vendor_multimodal_api_key to your own key value.

parser = LlamaParse(
parse_mode="parse_page_with_lvm",
model="openai-gpt4o",
vendor_multimodal_api_key="sk-proj-xxxxxx"
)


Note on Gemini model in EU SAAS: In our EU SAAS you need to provide a vertex AI certificate (as a string), for a valid project in europe-west1 google region.

You also have the possibility to use your own Azure Model Deployment using the following parameters:

parser = LlamaParse(
use_vendor_multimodal_model=True,
azure_openai_deployment_name="llamaparse-gpt-4o",
azure_openai_endpoint="https://<org>.openai.azure.com/openai/deployments/<dep>/chat/completions?api-version=<ver>",
azure_openai_api_version="2024-02-15-preview",
azure_openai_key="xxx"
)





By Setting gpt4o_mode to True LlamaParse will use openAI GPT4-o to do the document reconstruction. This is still working, but we recommend using use_vendor_multimodal_model to True and vendor_multimodal_model_name to openai-gpt4o instead.

The parameter gpt4o_api_key is still working but we recommend using the parameter vendor_multimodal_api_key instead.

Note for AI agents: this documentation is built for programmatic access. - Overview of all docs: https://developers.llamaindex.ai/llms.txt - Any page is available as raw Markdown by appending index.md to its URL — e.g. https://developers.llamaindex.ai/llamaparse/parse/getting_started/index.md - Agent-friendly REST search APIs live under https://developers.llamaindex.ai/api/ — search (BM25 full-text), grep (regex), read (fetch a page), and list (browse the doc tree). See https://developers.llamaindex.ai/llms.txt for parameters. - A hosted documentation MCP server is available at https://developers.llamaindex.ai/mcp. If you support MCP, you can ask the user to install it for browsing these docs directly (an alternative to the REST API). Setup: https://developers.llamaindex.ai/python/shared/mcp/