LlamaIndex pricing guide details
Pricing Overview
LlamaIndex sells its commercial document-parsing service, LlamaParse, on a freemium, credit-based model. There is a free tier at $0/month, a paid entry point at $50/month, and a custom-quoted Enterprise tier. The open-source LlamaIndex framework itself remains free to use — what you pay for is the managed parsing service and the credits it consumes.
The structure is unusually transparent for this category. Credits are the single billing unit, priced at 1,000 credits per $1.25, and each paid plan bundles a credit allowance: Starter includes 40K credits for $50/month, Pro includes 400K credits for $500/month.
Run the arithmetic and something important falls out. At Starter, $50 ÷ 40,000 credits = $1.25 per 1,000 credits. At Pro, $500 ÷ 400,000 credits = $1.25 per 1,000 credits. The included credits are priced at exactly the published pay-as-you-go rate at both paid tiers. There is no volume discount on credits built into the tier ladder. Moving from Starter to Pro buys you a larger prepaid block at the same unit price, not a cheaper one. Whatever else Pro includes beyond credits is not specified in the data we have, so the upgrade decision should be driven by those unlisted platform features — not by an expectation of cheaper throughput.
For buyers, this means the pricing question is simpler than usual: forecast your monthly credit consumption, multiply by $1.25 per 1,000, and you have your bill. The harder question — how many credits a given document consumes — is the part the pricing page does not answer for you.
Plan Comparison
| Plan | Price | Included Credits |
|---|---|---|
| Free | $0/month | 10K credits |
| Starter | $50/month | 40K credits |
| Pro | $500/month | 400K credits |
| Enterprise | Custom pricing | Not published |
The official pricing page lists the following for the Free plan: Europe (region availability), 10K credits, the ability to upgrade to Starter for pay-as-you-go credits, 100 users, and basic support. Feature contents for Starter, Pro, and Enterprise beyond their credit allowances are not published in the data we hold — we are not going to guess at them. Enterprise requires a custom quote.
Note that 100 users on the free tier is a genuinely generous seat allowance. Many tools in this category gate seats aggressively at the free tier (Dify's Sandbox tier, for comparison, is 1 member). LlamaIndex instead gates on consumption. That is a meaningful signal about the commercial model: seats are not the lever, credits are.
Hidden Costs and Considerations
Credits per page are not a published constant. This is the single largest unknown in any LlamaParse budget. Parsing cost varies by mode — richer extraction (tables, layout reconstruction, multimodal or LLM-assisted parsing) costs more credits per page than basic text extraction. Our pricing data does not include a credits-per-page figure for any mode, so we cannot convert your document volume into a dollar figure. Before committing, run a representative sample of your actual documents through the free 10K credits and measure consumption directly. A sample of your real PDFs is worth more than any vendor benchmark.
Reprocessing is a real and recurring cost. Parsing is rarely one-and-done. You will reprocess when you change chunking strategy, switch parse modes, fix an extraction bug, or re-index after a schema change. Every reprocess spends credits again. Teams routinely underestimate this by a factor of two or more in year one. Budget for your document corpus to be parsed several times, not once.
Credits are only part of the RAG bill. LlamaParse handles ingestion. The surrounding pipeline carries its own costs that LlamaIndex does not charge for and therefore will not appear on this invoice: embedding model API calls, vector database hosting, LLM inference at query time, and object storage for source documents. In production RAG systems, query-time LLM inference frequently exceeds parsing spend. Model your total cost of ownership across all four, not just the parsing line.
Expiry and rollover terms are not published. Whether unused included credits roll to the next month is not stated in our data. If your document volume is bursty — quarterly filings, annual report cycles, periodic bulk migrations — ask this question directly during evaluation. Non-rolling credits on a bursty workload mean you pay for a peak-sized plan every month.
Data residency. Europe is listed as a Free-tier attribute. If you have EU or other regional residency requirements, confirm which regions are available on your intended tier and whether that affects pricing.
The open-source escape hatch. The LlamaIndex framework is open source. If parsing costs grow uncomfortable, you retain the option to swap in a self-hosted parser while keeping your orchestration code. That optionality is worth real money as leverage — and it is a genuine architectural advantage over fully proprietary alternatives.
Cost Estimates by Team Size
All figures below use the published rate of $1.25 per 1,000 credits and the published plan allowances. Overage is assumed to bill at the same published pay-as-you-go rate; confirm overage terms with LlamaIndex before relying on this.
| Scenario | Working | Monthly Cost |
|---|---|---|
| Evaluation / pilot | Free plan, 10,000 included credits at $0 | $0 |
| Light production, 40K credits | Starter at $50/month, 40,000 credits included | $50 |
| Growing, 100K credits | Starter $50 + 60,000 overage credits at $1.25/1,000 ($75) | $125 |
| Mid-volume, 400K credits | Pro at $500/month, 400,000 credits included | $500 |
| High-volume, 1M credits | Pro $500 + 600,000 overage credits at $1.25/1,000 ($750) | $1,250 |
The crossover point is straightforward: because the unit rate is identical at both tiers, Starter-plus-overage and Pro cost the same for any given credit volume. Choose Pro for what it includes beyond credits, or for billing predictability — not for a lower rate.
How LlamaIndex Pricing Compares
| Tool | Pricing Model | Starting Price | Best For |
|---|---|---|---|
| LlamaIndex (LlamaParse) | Freemium, credit-based usage; open-source framework | $0 free (10K credits); $50/month Starter | Teams whose primary cost driver is document ingestion and parsing quality for RAG |
| Dify | Open source with paid cloud tiers | $0 Sandbox (200 message credits, 1 workspace, 1 member, 5 apps, 50MB knowledge storage); $59/month per workspace Professional | Teams wanting a visual LLM app builder with a self-host option; note per-workspace billing |
| CrewAI | Freemium, per-execution | $0 free (50 executions/month); $0.50 per additional execution | Multi-agent orchestration where work is naturally counted in discrete runs |
| Flowise | Freemium, self-host or cloud | $0 self-hosted (open source, MIT); $0 Cloud Free (2 flows, 100 predictions/month, 5MB storage) | Teams prioritizing zero-cost self-hosting with a low-friction visual builder |
These tools are not strict substitutes. Dify and Flowise are visual application builders; CrewAI is agent orchestration; LlamaIndex's commercial offering is document ingestion. Compare the billing units carefully — credits, message credits, executions, and predictions are not interchangeable, and any cross-tool cost comparison that ignores this is meaningless.
Two structural differences are worth flagging. First, Dify's Professional tier bills per workspace at $59/month — if your organization runs multiple isolated teams, that multiplies in a way LlamaIndex's 100-user free allowance does not. Second, both Dify and Flowise offer genuine self-hosting (Flowise under MIT), meaning the software cost can go to zero and be replaced by infrastructure cost. LlamaParse is a managed service; the LlamaIndex framework is open source, but the parsing service is not something you run yourself for free.
Our overall read: LlamaIndex's pricing is honest and easy to model, with an entry price ($50/month) low enough that the evaluation risk is trivial. The flat $1.25 per 1,000 credits across tiers is a fair, if unaggressive, structure — heavy users should raise volume pricing during an Enterprise conversation, since the published ladder offers no automatic break. The real budgeting work is not reading the price list; it is measuring credits-per-document on your own corpus during the free tier.