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Machine Learning · head to head

LlamaIndex vs Seldon

LlamaIndex logo

LlamaIndex

Machine Learning

Data framework for LLM applications

From
Free
Rated
-
Full reviewWebsite
Seldon logo

Seldon

Machine Learning

Kubernetes model serving whose current version is licensed under the Business Source Licence

From
Free
Rated
-
Full reviewWebsite

The short version

  • 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; Seldon seldon Core v2 is under the Business Source Licence rather than Apache 2.0, so production use requires a commercial agreement, and a team that evaluated it believing it was open source discovers the licence is the blocker exactly when the project is ready to ship.
  • They diverge on capability: LlamaIndex covers Data connectors, Seldon covers Kubernetes custom resources.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which LlamaIndex and Seldon actually diverge.

Attributes where LlamaIndex and Seldon differ
AttributeLlamaIndexSeldon
Pricing modelusage-basedfreemium
PlatformsLinux, Mac, WindowsLinux
Founded20222014

Identical on both: starting price (Free), free tier (Yes), 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 Seldon

  • Kubernetes custom resources
  • Inference graphs
  • Traffic strategies
  • Open Inference Protocol
  • Alibi Explain
  • Alibi Detect
  • Kafka-backed pipelines in v2
  • Commercial control plane

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 Seldon
  • Building retrieval augmented generation pipelines over private datanot Seldon
  • Indexing and querying enterprise documents from an LLM applicationnot Seldon

Seldon

  • Serving an ensemble or a multi-stage inference path as one versioned deployment rather than as a chain of separate servicesnot LlamaIndex
  • Running genuine production experiments where a share of live traffic goes to a candidate model and the results are comparednot LlamaIndex
  • Regulated environments needing explanations and drift monitoring attached to the served model rather than bolted on laternot LlamaIndex
  • Organisations with an established Kubernetes platform team who want serving expressed as manifests under existing deployment controlsnot 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

Seldon

  • Seldon Core v2 is under the Business Source Licence rather than Apache 2.0, so production use requires a commercial agreement, and a team that evaluated it believing it was open source discovers the licence is the blocker exactly when the project is ready to ship.
  • Core v1 remains Apache 2.0 but is in maintenance, so taking the free route means running software that receives no new development while the architecture it belongs to moves on without it.
  • Version 2 is a different system rather than a newer release, with different custom resources, a scheduler component and a Kafka-based pipeline model, so migrating from v1 is a re-implementation of every deployment manifest rather than an upgrade.
  • Kafka is a dependency for v2 pipelines, so an organisation that does not already operate it takes on a distributed log with its own storage, retention, rebalancing and failure modes purely in order to serve models.
  • Everything assumes Kubernetes fluency and the failure modes are Kubernetes failure modes, custom resource version mismatches, an operator that will not reconcile, admission webhooks and resource limits terminating an inference pod mid-request, so it needs a platform engineer rather than a data scientist.

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

Seldon

Free
  • Seldon CoreFree
    • Open source
    • Kubernetes deployment
    • Model serving
  • Seldon DeployFree
    • Enterprise features
    • GUI
    • Monitoring

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 Seldon if

  • You need kubernetes custom resources.
  • You want to start without paying.
  • You work on Linux.
  • You also want inference graphs.
Seldon review

Questions people ask

Is LlamaIndex or Seldon better?
Neither clearly leads. LlamaIndex starts at Free and Seldon at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, LlamaIndex or Seldon?
LlamaIndex starts at Free and Seldon at Free.
Does LlamaIndex or Seldon run on more platforms?
LlamaIndex runs on Linux, Mac, Windows. Seldon runs on Linux.
Can I use LlamaIndex for free?
Both have a free tier, so you can try either at no cost before committing.
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 Seldon is typically brought in for.
What can LlamaIndex do that Seldon cannot?
LlamaIndex covers Data connectors, Indexing, Query engine, RAG pipelines. Seldon covers Kubernetes custom resources, Inference graphs, Traffic strategies, Open Inference Protocol.

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
Seldon: Is Seldon open source?

Partly, and this is the thing to check before you build on it. Core v1 is Apache 2.0 but in maintenance. Core v2 was moved to the Business Source Licence in 2024, which allows evaluation but not unlicensed production use. Verify the current licence of each component you intend to run, including MLServer and the Alibi libraries.

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
Seldon: What is the difference between v1 and v2?

Architecture, not just version number. v2 introduces a scheduler, a different set of custom resources and Kafka-backed pipelines. Manifests, mental model and operations all change, so treat a move as a project.

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
Seldon: Do I need Kubernetes?

Yes. It is a Kubernetes-native system and there is no meaningful deployment without a cluster and someone competent to run it.

Seldon: What is MLServer?

Seldon's Python inference server implementing the Open Inference Protocol, usable inside Seldon deployments or on its own. Check its current licence alongside Core's, since the company has moved projects onto the Business Source Licence.

Seldon: Do I have to run Kafka?

For v2 pipelines, yes. If you only need single models served, that dependency is a large amount of infrastructure for the benefit, and a simpler serving layer may be the better answer.

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