Softwr

AI · head to head

Galileo vs OpenAI API

Galileo logo

Galileo

AI

Evaluation and observability platform for GenAI applications and agents

From
Free
Free plan
Yes
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
Free plan
No
Full reviewWebsite

The short version

  • Only Galileo has a free tier, so it costs nothing to try first.
  • Each has a real cost: Galileo the free plan is limited to 5,000 traces per month, which is quickly outgrown by production workloads.; 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: Galileo covers Pre-built evaluations, 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 Galileo and OpenAI API actually diverge.

Attributes where Galileo and OpenAI API differ
AttributeGalileoOpenAI API
Starting priceFree$0.15/per-million-tokens
Pricing modelfreemiumusage-based
Free tierYesNo
Platformsweb, apiApi
CategoryAIMachine Learning
FoundedUnknown2015

Identical on both: user rating (Not yet rated).

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 Galileo

  • Pre-built evaluations
  • Ground truth capture
  • Luna models
  • Agent behavior analysis
  • Production guardrails
  • Flexible deployment

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.

Galileo

  • Evaluating RAG and agent applications before production releasenot OpenAI API
  • Monitoring live GenAI applications for failures and driftnot OpenAI API
  • Applying real-time guardrails without custom integration worknot OpenAI API
  • Reducing evaluation costs using distilled Luna judge modelsnot 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 Galileo
  • Retrieval-augmented question answering over internal documents, using the embedding and generation models togethernot Galileo
  • Extracting structured records from unstructured text, where schema-constrained output removes most of the parsing problemnot Galileo
  • Prototyping a language feature quickly to find out whether it is worth the cost of a self-hosted alternative laternot Galileo

Where each one falls short

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

Galileo

  • The free plan is limited to 5,000 traces per month, which is quickly outgrown by production workloads.
  • Real-time guardrails and unlimited trace capacity are reserved for the custom-priced Enterprise tier.
  • Pro plan pricing scales with trace volume, so costs can grow unpredictably as usage increases.
  • On-premises deployment requires an Enterprise contract rather than being available self-serve.

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

Galileo

Free
  • FreeFree
    • 5,000 traces/month
    • Unlimited users
    • Unlimited custom evaluations
  • Pro$100/month
    • 50,000 traces/month
    • Standard role-based access control
    • Advanced analytics and insights
  • Enterprise$undefined/mo
    • Unlimited trace capacity
    • Custom rate limits
    • Hosted, VPC, or on-prem deployment

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 Galileo if

  • You need pre-built evaluations.
  • You want to start without paying.
  • You work on web, api.
  • You also want ground truth capture.
Galileo 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 Galileo or OpenAI API better?
Neither clearly leads. Galileo 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, Galileo or OpenAI API?
Galileo has a free tier; the other does not. Paid plans start at Free for Galileo and $0.15/per-million-tokens for OpenAI API.
Does Galileo or OpenAI API run on more platforms?
Galileo runs on web, api. OpenAI API runs on Api.
Can I use Galileo for free?
Yes. Galileo has a free tier, so you can try it without paying. OpenAI API starts at $0.15/per-million-tokens.
What is Galileo best used for?
Galileo is most often used for evaluating rag and agent applications before production release, monitoring live genai applications for failures and drift, applying real-time guardrails without custom integration work, reducing evaluation costs using distilled luna judge models. Of those, evaluating rag and agent applications before production release and monitoring live genai applications for failures and drift are not what OpenAI API is typically brought in for.
What can Galileo do that OpenAI API cannot?
Galileo covers Pre-built evaluations, Ground truth capture, Luna models, Agent behavior analysis. OpenAI API covers Text and reasoning models, Embeddings, Speech and audio, Image generation.

Answered from the vendors’ own pages

Galileo: What does Galileo cost?

Galileo offers a free plan, a Pro plan at $100/month billed yearly (with a 33% annual discount), and a custom-priced Enterprise plan for unlimited trace capacity.

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.

Galileo: Is there a free plan, and what are its limits?

The Free plan includes 5,000 traces per month with unlimited users and unlimited custom evaluations, aimed at developers and small teams experimenting with GenAI.

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.

Galileo: How is usage metered?

Galileo's pricing scales based on the number of traces processed each month, with Free capped at 5,000, Pro at 50,000, and Enterprise offering unlimited trace capacity.

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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