Machine Learning · head to head
OpenAI API vs OpenRouter

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
- -

OpenRouter
Machine Learning
Unified API gateway routing requests across 500+ models from 80+ providers
- From
- Free
- Rated
- -
The short version
- Only OpenRouter 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.; OpenRouter no free tier; all usage incurs cost
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which OpenAI API and OpenRouter actually diverge.
| Attribute | OpenAI API | OpenRouter |
|---|---|---|
| Starting price | $0.15/per-million-tokens | Free |
| Free tier | No | Yes |
| Platforms | Api | API, Web |
| Founded | 2015 | Unknown |
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 OpenAI API
- Text and reasoning models
- Embeddings
- Speech and audio
- Image generation
- Function calling
- Structured outputs
- Batch processing
- Prompt caching
Only in OpenRouter
Nothing recorded that OpenAI API does not also cover.
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 OpenRouter
- Retrieval-augmented question answering over internal documents, using the embedding and generation models togethernot OpenRouter
- Extracting structured records from unstructured text, where schema-constrained output removes most of the parsing problemnot OpenRouter
- Prototyping a language feature quickly to find out whether it is worth the cost of a self-hosted alternative laternot OpenRouter
OpenRouter
- Multi-model applications optimising for cost or performancenot OpenAI API
- Provider-agnostic deployments avoiding vendor lock-innot OpenAI API
- Enterprise applications with custom data policies and provider requirementsnot OpenAI API
- Development workflows testing multiple models without code changesnot 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.
OpenRouter
- No free tier; all usage incurs cost
- Pricing varies by model; specific rates not published on main site without account access
- Adds latency through additional routing layer compared to direct provider APIs
- Dependent on upstream provider uptime and API compatibility
Pricing, plan by plan
OpenAI API
$0.15/per-million-tokens- GPT-4o mini$0.15/per-million-input-tokens
- Fast
- Affordable
- GPT-4o$5/per-million-input-tokens
- Multimodal
- 128K context
OpenRouter
Free- FreeFree
- 50 requests per day
- Access to 25+ free models across 4 providers
- Community support
- Pay-as-you-go$null/variable
- 5.5% platform fee on inference costs
- Access to 500+ models across 80+ providers
- Email support
- Enterprise$null/custom
- Negotiable platform fees
- 200,000 USD of list price inference per month with no fees, then 5% fee after
- SSO/SAML support
Which should you pick?
Choose OpenAI API if
- You need text and reasoning models.
- You work on Api.
- You also want embeddings.
Questions people ask
- Is OpenAI API or OpenRouter better?
- Neither clearly leads. OpenAI API starts at $0.15/per-million-tokens and OpenRouter at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, OpenAI API or OpenRouter?
- OpenRouter has a free tier; the other does not. Paid plans start at $0.15/per-million-tokens for OpenAI API and Free for OpenRouter.
- Does OpenAI API or OpenRouter run on more platforms?
- OpenAI API runs on Api. OpenRouter runs on API, Web.
- Can I use OpenRouter for free?
- Yes. OpenRouter 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 OpenRouter is typically brought in for.
- What can OpenAI API do that OpenRouter cannot?
- OpenAI API covers Text and reasoning models, Embeddings, Speech and audio, Image generation.
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.
OpenRouter: How much does OpenRouter charge?
OpenRouter charges a 5.5% platform fee on top of the actual inference costs from selected models. Customers purchase credits on a pay-as-you-go basis with no subscriptions or minimum spend requirements.
SourceOpenAI 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.
OpenRouter: Is there a free tier?
Yes. OpenRouter offers a free tier with 50 requests per day and access to 25+ free models across 4 providers. The free tier provides community support only.
SourceOpenAI 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.
OpenRouter: What does the Enterprise plan include?
The Enterprise plan includes 200,000 USD of list price inference per month at no cost, with a 5% platform fee applied to usage above that threshold. It also includes SSO/SAML support, contractual SLAs, and dedicated support with a shared Slack channel.
SourceOpenAI 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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