PDF to Markdown vs LlamaParse
LlamaParse is a powerful GenAI-native parsing cloud built for LlamaIndex RAG pipelines. pdf2md.dev is a hosted converter you can use free and anonymously – in the browser, by REST API, or from a hosted MCP. Here is an honest side-by-side.
Credit-metered RAG cloud, or free hosted conversion
Choose LlamaParse when you are building a RAG pipeline inside LlamaIndex and want GenAI-native parsing modes for very complex documents – it is a cloud API, billed per page in credits, that needs an account and an API key. Choose pdf2md.dev when you want clean Markdown now with no sign-up: a free anonymous browser tool, built-in OCR, real Markdown tables and formulas, and a REST API plus a hosted MCP any agent can call.
pdf2md.dev vs LlamaParse, feature by feature
Both turn PDFs into clean Markdown for LLMs. The difference is no-account-and-free versus a credit-metered cloud API.
| pdf2md.dev | LlamaParse | |
|---|---|---|
| Shape | Hosted service – browser, REST API or hosted MCP | Hosted cloud parsing API (LlamaIndex-native) |
| Account | None to convert | Sign-up + API key required |
| Cost | Free anonymous tier; flat paid tiers | 10,000 free credits/mo (~3,300 pages); then credit-metered, plans from $50/mo |
| Pricing model | Flat tiers, predictable | Per-page credits by mode: Fast 1, Cost-effective 3, Agentic 10, Agentic Plus 45 |
| Markdown on free path | Yes on the free tier | Fast tier is spatial text only; Markdown needs the higher (costlier) modes |
| Scanned PDF OCR | Built in, many languages, no flags | Yes via GenAI parsing |
| Browser / no-code use | Yes – drop a file in the browser | API/SDK first; no anonymous web tool |
| Automation | REST API + hosted MCP, no key to start | REST API + SDK, tightly LlamaIndex-native |
| Files | Short retention; not used to train models | Uploaded to their cloud for processing |
LlamaParse credit tiers and free quota from its public pricing; pdf2md.dev values are the current free-tier limits. Both evolve – check each source for the latest.
More options? See the full roundup of the best PDF to Markdown converters for the whole field at a glance.
When LlamaParse is the better choice
LlamaParse is a strong, RAG-focused product. Reach for it when these fit.
Deep LlamaIndex RAG
You build retrieval pipelines in LlamaIndex and want parsing that plugs straight into that ecosystem.
Agentic parse modes
You have very complex documents that justify the Agentic or Agentic Plus modes and the per-page credit cost.
Already on the platform
You already use LlamaIndex Cloud and want parsing, indexing and retrieval billed together.
When pdf2md.dev fits better
No account, no credits to count, no SDK to wire up.
No account or API key
Convert anonymously in the browser on the free tier instead of signing up and provisioning a key.
Hosted MCP for any agent
Call a REST API or hosted MCP from any framework, not just one ecosystem.
Flat, predictable limits
Plain tiers instead of per-page credits that change with parse mode and document complexity.
OCR & tables built in
Scanned PDFs and tables are handled out of the box on the free path.
Building a RAG pipeline?
pdf2md.dev returns chunk-friendly Markdown from a REST API and a hosted MCP, so any agent or framework can ingest PDFs without an account. See the RAG guide and the Python tutorial.
Common questions
Is LlamaParse free?
New users get 10,000 credits per month. Credits are charged per page and vary by parsing mode, so that is roughly 3,300 pages on the cost-effective tier. Beyond that it is credit-metered, with paid plans from $50/month, and you need an account and an API key.
Do I need an account to use pdf2md.dev?
No. Convert anonymously in the browser on the free tier (3 slots, 10 MB files, a 15-minute time budget, 1-hour retention). LlamaParse requires a sign-up and an API key.
Does LlamaParse output Markdown for free?
Its Fast tier (1 credit) returns spatial text only, not Markdown. Markdown comes from the higher modes (cost-effective and up), which cost more credits per page. pdf2md.dev returns clean Markdown on the free tier.
Which is better for RAG?
LlamaParse is GenAI-native and integrates tightly with LlamaIndex pipelines. pdf2md.dev gives you clean, chunk-friendly Markdown plus a REST API and a hosted MCP that any agent or framework can call.
Can I call pdf2md.dev from an agent?
Yes, via a REST API and a hosted MCP endpoint, with no account to start. LlamaParse is API and SDK first and LlamaIndex-native.
What about scanned PDFs?
Both handle scanned PDFs. On pdf2md.dev OCR is built in across many languages with no flags to set – see converting scanned PDFs.