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Machine Learning · head to head

OpenAI API vs Together AI

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
Together AI logo

Together AI

AI

Open-source AI at scale

From
Free
Rated
-
Full reviewWebsite

The short version

  • Only Together AI 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.; Together AI free tier limits not clearly specified in pricing documentation
  • They diverge on capability: OpenAI API covers Text and reasoning models, Together AI covers Open-source models.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which OpenAI API and Together AI actually diverge.

Attributes where OpenAI API and Together AI differ
AttributeOpenAI APITogether AI
Starting price$0.15/per-million-tokensFree
Free tierNoYes
PlatformsApiApi, Cloud
CategoryMachine LearningAI
Founded20152022

Identical on both: pricing model (usage-based), 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
  • Speech and audio
  • Image generation
  • Function calling
  • Structured outputs
  • Batch processing
  • Prompt caching
  • Usage tiers and rate limits

Only in Together AI

  • Open-source models
  • Fast inference
  • REST API
  • Python SDK
  • OpenAI compatible
  • Api support
  • Cloud support

Both cover

  • Embeddings
  • Fine-tuning

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 Together AI
  • Retrieval-augmented question answering over internal documents, using the embedding and generation models togethernot Together AI
  • Extracting structured records from unstructured text, where schema-constrained output removes most of the parsing problemnot Together AI
  • Prototyping a language feature quickly to find out whether it is worth the cost of a self-hosted alternative laternot Together AI

Together AI

  • LLM inference for production AI applicationsnot OpenAI API
  • Content generation at scalenot OpenAI API
  • Code execution and embeddingsnot OpenAI API
  • Model fine-tuning and trainingnot OpenAI API
  • Startup and enterprise AI deploymentnot 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.

Together AI

  • Free tier limits not clearly specified in pricing documentation
  • Pricing varies significantly by model and use case
  • Requires account setup for production access
  • Batch API discounts apply only to non-urgent workloads

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

Together AI

Free
  • Serverless Inference$0.03/1M input tokens
    • Chat and Vision models
    • Image generation
    • Video generation
  • Provisioned Throughput$21600/month
    • Up to 83% savings vs commercial alternatives
    • Reserved capacity
    • Guaranteed throughput
  • Dedicated Inference$5.49/hour
    • H100 GPU instance
    • Single-tenant deployment
    • No resource sharing
  • GPU Clusters$3.99/GPU-hour
    • On-demand capacity
    • Volume discounts available
    • Reserved options with up to 35% savings

Which should you pick?

Choose OpenAI API if

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

Choose Together AI if

  • You need open-source models.
  • You want to start without paying.
  • You work on Api, Cloud.
  • You also want fast inference.
Together AI review

Questions people ask

Is OpenAI API or Together AI better?
Neither clearly leads. OpenAI API starts at $0.15/per-million-tokens and Together AI at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, OpenAI API or Together AI?
Together AI has a free tier; the other does not. Paid plans start at $0.15/per-million-tokens for OpenAI API and Free for Together AI.
Does OpenAI API or Together AI run on more platforms?
OpenAI API runs on Api. Together AI runs on Api, Cloud.
Can I use Together AI for free?
Yes. Together AI 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 Together AI is typically brought in for.
What can OpenAI API do that Together AI cannot?
OpenAI API covers Text and reasoning models, Speech and audio, Image generation, Function calling. Together AI covers Open-source models, Fast inference, REST API, Python SDK. Both handle Embeddings, Fine-tuning.

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.

Together AI: Does Together AI offer a free tier?

Yes, Together AI advertises 'Start for free, scale on demand,' but specific free tier usage limits are not detailed on the pricing page.

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.

Together AI: What are Together AI's highest model prices?

Serverless inference pricing ranges from free for base models up to $4.40 per 1M input tokens for premium models. Video generation costs $0.14 to $3.20 per video depending on resolution.

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.

Together AI: How much can I save with Provisioned Throughput?

Together AI offers up to 83% savings compared to commercial alternatives when using their Provisioned Throughput option with reserved capacity.

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.

Together AI: What is Together AI's fine-tuning pricing?

Standard fine-tuning costs $0.48 to $2.90 per 1M tokens depending on model size, with a minimum charge of $4.00 per job.

Source
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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