LlamaParse — pricing, limits & comparison
Generated 2026-11-03 22:50 UTC · JSON
LlamaParse scores 78.92 for bulk text/markdown extraction for rag (PDF & document extraction). Agent-friction 80/100.
Pricing
| Plan | Base / mo | Included | Overage |
|---|---|---|---|
| Balanced mode (per-page, credit-metered) | $0 | 3.333k pages | $0.00/1 pages |
Cost at scale — PDF & document extraction
| Layout parse (10k pages/mo) |
|---|
| $25 |
Agent-friction breakdown — 80/100
| Check | Points | Pass |
|---|---|---|
| Test credentials without a credit card | 20 | ✓ |
| Sandbox or test mode | 15 | ✓ |
| Setup with no human-only steps | 15 | ✓ |
| Official CLI | 10 | × |
| Official MCP server | 10 | × |
| Markdown docs, current with the SDK | 10 | ✓ |
| Typed SDK for main languages | 10 | ✓ |
| Error messages that name the fix | 10 | ✓ |
Official SDKs
Python (llama-cloud-services) · Python (llama-parse) · TypeScript (llama-cloud-services)
Health & reliability — 85/100
| Incidents (90 days) | 0 |
| Changelog entries (90 days) | 0 |
| Deprecations (90 days) | 0 |
| Downloads trend | -22.4% (llama-cloud-services on pypi) |
| Last release | 2026-02-13 |
| Ownership events (90 days) | 0 |
Sources: pypi.org · developers.llamaindex.ai. Captured 2026-11-03.
What the internet says Unverified · aggregated from public posts
Sentiment: mixed. This is summarized from public posts, is not fact-checked, and never affects the score.
- other (neutral): “LlamaParse is an agentic OCR platform built for semantic reconstruction of complex documents into RAG-ready data; Reducto edges it on complex-doc accuracy in several comparisons.” — blog
- pricing (neutral): “Credit-metered modes range from Fast to Agentic Plus, a ~45x price spread; teams watch costs when defaulting to the agentic modes.” — blog
- other (positive): “On RealDoc-Bench, LlamaParse Agentic scores 92.1% field-level Q&A accuracy — competitive, behind Extend Parse 2.0 at 95.7%.” — blog