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Machine Learning · head to head

LlamaIndex vs OpenAI API

LlamaIndex logo

LlamaIndex

Machine Learning

Data framework for LLM applications

From
Free
Rated
-
Full reviewWebsite
OpenAI API logo

OpenAI API

Machine Learning

Hosted API for OpenAI's language, embedding, image and audio models, billed per token

From
$0.15/per-million-tokens
Rated
-
Full reviewWebsite

The short version

  • Only LlamaIndex has a free tier, so it costs nothing to try first.
  • Each has a real cost: LlamaIndex the free LlamaCloud plan includes 10K credits and has no pay as you go option, so work stops when credits run out; OpenAI API cost scales with tokens rather than with seats, so a successful feature's bill grows with its adoption, and an interface that lets users paste long documents has no natural ceiling on spend unless you build one yourself.
  • They diverge on capability: LlamaIndex covers Data connectors, OpenAI API covers Text and reasoning models.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which LlamaIndex and OpenAI API actually diverge.

Attributes where LlamaIndex and OpenAI API differ
AttributeLlamaIndexOpenAI API
Starting priceFree$0.15/per-million-tokens
Free tierYesNo
PlatformsLinux, Mac, WindowsApi
Founded20222015

Identical on both: pricing model (usage-based), user rating (Not yet rated), category (Machine Learning).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in LlamaIndex

  • Data connectors
  • Indexing
  • Query engine
  • RAG pipelines
  • Agents
  • OpenAI
  • Anthropic
  • Pinecone

Only in OpenAI API

  • Text and reasoning models
  • Embeddings
  • Speech and audio
  • Image generation
  • Function calling
  • Structured outputs
  • Batch processing
  • Prompt caching

What people use each for

The jobs each tool is most often brought in to do.

LlamaIndex

  • Parsing PDFs and complex documents into structured text for RAGnot OpenAI API
  • Building retrieval augmented generation pipelines over private datanot OpenAI API
  • Indexing and querying enterprise documents from an LLM applicationnot OpenAI API

OpenAI API

  • Adding summarisation, drafting or classification to an existing product where building a model would take longer than the product's whole roadmapnot LlamaIndex
  • Retrieval-augmented question answering over internal documents, using the embedding and generation models togethernot LlamaIndex
  • Extracting structured records from unstructured text, where schema-constrained output removes most of the parsing problemnot LlamaIndex
  • Prototyping a language feature quickly to find out whether it is worth the cost of a self-hosted alternative laternot LlamaIndex

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

LlamaIndex

  • The free LlamaCloud plan includes 10K credits and has no pay as you go option, so work stops when credits run out
  • Concurrent parse jobs are capped at 5 on Free and Starter, 20 on Pro and 100 on Enterprise
  • Pay as you go spend is capped at $500 per month on Starter and $5,000 per month on Pro
  • Enterprise SSO is Enterprise plan only
  • Volume discounts on credits and 5x higher rate limits are Enterprise only
  • SaaS or hybrid cloud deployment choice and a dedicated account manager are Enterprise only
  • Enterprise pricing is by quote with no published rate

OpenAI API

  • Cost scales with tokens rather than with seats, so a successful feature's bill grows with its adoption, and an interface that lets users paste long documents has no natural ceiling on spend unless you build one yourself.
  • Models are deprecated on the vendor's timetable, and a fine-tuned model built on a retired base goes with it, so the tuning work and the data curation behind it must be redone rather than migrated.
  • Behaviour shifts between model versions in ways no test catches unless you wrote one, so prompts tuned over months against a particular snapshot can regress quietly on migration, which makes an evaluation suite a prerequisite rather than an improvement.
  • It cannot run inside your own network, so data residency requirements, air-gapped environments and contracts forbidding third-party processing rule it out regardless of the provider's own security posture.
  • You inherit its availability and its rate limits, so a provider incident is an outage in your product and a traffic spike can be throttled at precisely the moment the feature is proving itself.

Pricing, plan by plan

LlamaIndex

Free
  • FreeFree
    • 10K monthly credits
    • Basic parsing
    • 5 concurrent jobs
  • Starter$50/month
    • 40K credits + pay-as-you-go
    • Up to 400K credits
    • 5 concurrent jobs
  • Pro$500/month
    • 400K credits + limited-time bonus
    • 20 concurrent jobs
    • Priority Slack support
  • Enterprise$null/custom
    • Custom volume discounts
    • 5x higher rate limits
    • SSO

OpenAI API

$0.15/per-million-tokens
  • GPT-4o mini$0.15/per-million-input-tokens
    • Fast
    • Affordable
  • GPT-4o$5/per-million-input-tokens
    • Multimodal
    • 128K context

Which should you pick?

Choose LlamaIndex if

  • You need data connectors.
  • You want to start without paying.
  • You work on Linux, Mac, Windows.
  • You also want indexing.
LlamaIndex review

Choose OpenAI API if

  • You need text and reasoning models.
  • You work on Api.
  • You also want embeddings.
OpenAI API review

Questions people ask

Is LlamaIndex or OpenAI API better?
Neither clearly leads. LlamaIndex starts at Free and OpenAI API at $0.15/per-million-tokens, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, LlamaIndex or OpenAI API?
LlamaIndex has a free tier; the other does not. Paid plans start at Free for LlamaIndex and $0.15/per-million-tokens for OpenAI API.
Does LlamaIndex or OpenAI API run on more platforms?
LlamaIndex runs on Linux, Mac, Windows. OpenAI API runs on Api.
Can I use LlamaIndex for free?
Yes. LlamaIndex has a free tier, so you can try it without paying. OpenAI API starts at $0.15/per-million-tokens.
What is LlamaIndex best used for?
LlamaIndex is most often used for parsing pdfs and complex documents into structured text for rag, building retrieval augmented generation pipelines over private data, indexing and querying enterprise documents from an llm application. Of those, parsing pdfs and complex documents into structured text for rag and building retrieval augmented generation pipelines over private data are not what OpenAI API is typically brought in for.
What can LlamaIndex do that OpenAI API cannot?
LlamaIndex covers Data connectors, Indexing, Query engine, RAG pipelines. OpenAI API covers Text and reasoning models, Embeddings, Speech and audio, Image generation.

Answered from the vendors’ own pages

LlamaIndex: How much does LlamaIndex (LlamaParse) cost?

LlamaIndex offers a Free plan with 10K monthly credits at $0/month. The Starter plan is $50/month for 40K credits plus pay-as-you-go overage up to 400K total. The Pro plan is $500/month for 400K credits. Credits are priced at 1,000 credits for $1.25.

Source
OpenAI API: Is my data used to train the models?

API inputs and outputs are not used for training by default, which differs from the consumer product. Retention periods and enterprise terms change, so read the current data usage policy rather than trusting a summary.

LlamaIndex: Is LlamaIndex free?

Yes, LlamaIndex offers a free plan with 10K monthly credits, basic parsing, 5 concurrent jobs, and support for up to 100 users with no upfront payment required.

Source
OpenAI API: Can I run these models on my own hardware?

No. The weights are not distributed. If self-hosting is a requirement, you are looking at open-weight models instead, with the operational and quality trade-offs that implies.

LlamaIndex: What are LlamaIndex's concurrent job limits?

The Free and Starter plans allow 5 concurrent jobs. The Pro plan increases this to 20 concurrent jobs. Enterprise plans offer custom configurations with 5x higher rate limits.

Source
OpenAI API: How is it priced?

Per token, with input and output priced differently and each model priced differently. Batch processing and cached input prefixes reduce it. The practical consequence is that your bill is a function of prompt design, not just of request count.

OpenAI API: What is the difference from Azure OpenAI Service?

The same model family delivered by Microsoft under an Azure contract, with Azure identity, networking and regional controls, and a different release cadence for new models. Enterprises with an Azure agreement often choose it for procurement and data residency reasons rather than technical ones.

OpenAI API: How do I keep the cost under control?

Cap input length, cache repeated prefixes, route easy requests to smaller models, use the batch path where latency does not matter, and set per-user limits before launch rather than after the first surprising invoice.

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