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Machine Learning · head to head

OpenAI API vs Vellum

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
Vellum logo

Vellum

AI

Personalized AI assistant with persistent memory and autonomous action-taking

From
Free
Free plan
Yes
Full reviewWebsite

The short version

  • Only Vellum has a free tier, so it costs nothing to try first.
  • Each has a real cost: 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.; Vellum pricing varies significantly by computational tier, making budget planning difficult
  • They diverge on capability: OpenAI API covers Text and reasoning models, Vellum covers Persistent AI identity.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

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

Attributes where OpenAI API and Vellum differ
AttributeOpenAI APIVellum
Starting price$0.15/per-million-tokensFree
Pricing modelusage-basedFreemium with paid plans and pay-as-you-go credits
Free tierNoYes
PlatformsApiWeb, macOS, iOS, Slack, Telegram, Terminal
CategoryMachine LearningAI
Founded2015Unknown

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 OpenAI API

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

Only in Vellum

  • Persistent AI identity
  • Long-term memory
  • Email automation
  • Calendar management
  • Autonomous task execution
  • Multi-device synchronization
  • Custom plugins
  • Open-source deployment

What people use each for

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

OpenAI API

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

Vellum

  • Personal productivity automation across email and calendarnot OpenAI API
  • CRM updates and pipeline managementnot OpenAI API
  • Expense report generation and managementnot OpenAI API
  • Document drafting and content creationnot OpenAI API
  • Meeting scheduling and calendar coordinationnot OpenAI API

Where each one falls short

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

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.

Vellum

  • Pricing varies significantly by computational tier, making budget planning difficult
  • Requires explicit permission for sensitive actions, limiting autonomy
  • Self-hosting option may intimidate non-technical users
  • Learning curve to develop customizations with plugins

Pricing, plan by plan

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

Vellum

Free
  • FreeFree
    • Starter credits included
    • Basic features
  • Mighty$30/month
    • 1 vCPU, 2 GiB RAM
    • 10 GB storage
    • Included usage allowance
  • Super$100/month
    • 2.5 vCPU, 5 GiB RAM
    • 30 GB storage
    • Assistant email and subdomain
  • Ultra$200/month
    • 4 vCPU, 8 GiB RAM
    • 60 GB storage
    • Assistant email and subdomain

Which should you pick?

Choose OpenAI API if

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

Choose Vellum if

  • You need persistent ai identity.
  • You want to start without paying.
  • You work on Web, macOS, iOS, Slack, Telegram, Terminal.
  • You also want long-term memory.
Vellum review

Questions people ask

Is OpenAI API or Vellum better?
Neither clearly leads. OpenAI API starts at $0.15/per-million-tokens and Vellum at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, OpenAI API or Vellum?
Vellum has a free tier; the other does not. Paid plans start at $0.15/per-million-tokens for OpenAI API and Free for Vellum.
Does OpenAI API or Vellum run on more platforms?
OpenAI API runs on Api. Vellum runs on Web, macOS, iOS, Slack, Telegram, Terminal.
Can I use Vellum for free?
Yes. Vellum has a free tier, so you can try it without paying. OpenAI API starts at $0.15/per-million-tokens.
What is OpenAI API best used for?
OpenAI API is most often used for adding summarisation, drafting or classification to an existing product where building a model would take longer than the product's whole roadmap, retrieval-augmented question answering over internal documents, using the embedding and generation models together, extracting structured records from unstructured text, where schema-constrained output removes most of the parsing problem, prototyping a language feature quickly to find out whether it is worth the cost of a self-hosted alternative later. Of those, adding summarisation, drafting or classification to an existing product where building a model would take longer than the product's whole roadmap and retrieval-augmented question answering over internal documents, using the embedding and generation models together are not what Vellum is typically brought in for.
What can OpenAI API do that Vellum cannot?
OpenAI API covers Text and reasoning models, Embeddings, Speech and audio, Image generation. Vellum covers Persistent AI identity, Long-term memory, Email automation, Calendar management.

Answered from the vendors’ own pages

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.

Vellum: How does Vellum protect my data privacy?

Vellum uses permission-based controls requiring explicit approval for sensitive actions. Data is encrypted and the option for self-hosting provides complete data control. Open-source deployment option allows hosting on your own infrastructure.

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.

Vellum: Can I use Vellum for business team collaboration?

Vellum is primarily designed as a personal assistant with persistent identity. For team collaboration, platforms like Lindy offer better multi-user features with shared credit pools and Slack workspace integration.

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.

Vellum: What does the free tier include?

Vellum offers free starter credits to begin using the platform. Beyond that, it operates on a pay-as-you-go credit model with paid tiers starting at $30/month for increased computational resources and bundled credits.

Source
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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