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InferenceSaver vs Portkey

An AI gateway in front of your providers — compared with being the provider.

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InferenceSaver and Portkey are not the same kind of product, and the comparison only makes sense once that is said plainly. Portkey is a layer you put in front of the provider accounts you already pay. We are the account you pay. Almost every difference below follows from that one structural fact.

  • Whether the inference itself gets cheaper, or only better governed.
  • Whether there is a second bill for the layer sitting in front of your providers.
  • Whether image, video, and audio bill from the same balance or from whoever you proxy to.

Why teams move their spend to InferenceSaver

Watching the bill climb is not a strategy. These are the three things that change on day one.

The rate itself is lower

You buy inference from us at a discount to provider list rates, rather than paying list rate and adding a gateway on top.

Request traces showing original and discounted cost

One account, not two

No provider accounts to hold, no keys to rotate in a second place, and no second vendor invoice for the layer in front.

Browsing the model catalogue

Media on the same balance

Image, video, and audio generation bill from the credits that already cover your text calls.

Generating video from a prompt
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The table below keeps the rows where Portkey is clearly ahead rather than quietly dropping them. Guardrails, prompt management, and self-hosting are theirs, and a comparison that hid that would not be worth reading.

  • Where Portkey is the stronger product, the row says so.
  • Where the two do the same thing, the row says that too.
  • Every row is checkable against either product's own documentation.

Side by side

The axes that actually change the decision, with no attempt to hide the ones where Portkey is strong.

  • Primary job

    InferenceSaverCost control
    PortkeyGateway control
  • Who you buy inference from

    InferenceSaverOne balance
    PortkeyBring your own
  • What you pay for the layer

    InferenceSaverNo add-on
    PortkeyAdd-on
  • Per-request cost trace

    InferenceSaverOriginal vs paid
    PortkeyList rate
  • Spend attributed per member

    InferenceSaverYes
    PortkeyVia metadata
  • Guardrails and content checks

    InferenceSaverNot offered
    PortkeyCore feature
  • Prompt management

    InferenceSaverNot offered
    PortkeyCore feature
  • Retries, fallbacks, caching

    InferenceSaverRouting only
    PortkeyConfigurable
  • Self-hosting the layer

    InferenceSaverManaged
    PortkeyAvailable
  • OpenAI-compatible API

    InferenceSaverYes
    PortkeyYes
  • Workspace roles

    InferenceSaverYes
    PortkeyYes
  • Image generation

    InferenceSaverIncluded
    PortkeyProxied
  • Video generation

    InferenceSaverIncluded
    PortkeyNot offered
  • Audio generation

    InferenceSaverIncluded
    PortkeyNot offered
InferenceSaver vs Portkey
What you are comparingInferenceSaverPortkey
Primary jobCost controlGateway control
Who you buy inference fromOne balanceBring your own
What you pay for the layerNo add-onAdd-on
Per-request cost traceOriginal vs paidList rate
Spend attributed per memberYesVia metadata
Guardrails and content checksNot offeredCore feature
Prompt managementNot offeredCore feature
Retries, fallbacks, cachingRouting onlyConfigurable
Self-hosting the layerManagedAvailable
OpenAI-compatible APIYesYes
Workspace rolesYesYes
Image generationIncludedProxied
Video generationIncludedNot offered
Audio generationIncludedNot offered
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One-word verdicts are claims, not evidence. The three sections below take the rows that decide most migrations and show where they actually land: on the invoice, in a traced request, and on the bill for everything that is not text.

  • Cost — what changes about the number at the bottom of the invoice.
  • Observability — what a single request records once it has run.
  • Media — where image, video, and audio spend ends up.

Where the difference actually shows up

Three places the gap is visible in a workflow rather than a feature list.

Request traces showing original and discounted cost
Cost

The rate changes, not just the reporting

A gateway can tell you precisely what you spent at your provider's list rate. It cannot change that rate. Because the inference is bought here, every request carries the original provider rate and what you actually paid, side by side — and the second number is the lower one.

The rate changes, not just the reporting: InferenceSaver vs Portkey
CapabilityInferenceSaverPortkey
Discounted inference rateYesNot offered
Cost of the layer itselfNoneGateway pricing
Original vs paid on each requestSide by sideList rate
Vendor relationships to holdOneProvider plus gateway
See it in the dashboard
Request traces grouped by key and member
Observability

Traces that already know what you paid

Every call is traced with the model, latency, tokens, and cost, grouped by API key and by workspace member. Portkey's logging is deeper and more configurable than ours — what it cannot do is show a discounted rate, because it is not the one selling you the tokens.

Traces that already know what you paid: InferenceSaver vs Portkey
CapabilityInferenceSaverPortkey
Per-request traceYesYes
Attribution per memberYesVia metadata
Guardrails on request contentNot offeredYes
Prompt versioningNot offeredYes
See it in the dashboard
Generating video from a prompt in the studio
Beyond text

Image, video and audio on the same balance

Generation runs in the same studio and draws from the same credits as text. Through a gateway, media calls are proxied to whichever provider account covers them, so the spend lands on that provider's invoice rather than the one you were trying to consolidate.

Image, video and audio on the same balance: InferenceSaver vs Portkey
CapabilityInferenceSaverPortkey
Image generationIncludedProxied
Video generationIncludedNot offered
Audio generationIncludedNot offered
Shared credit balanceYesNot offered
See it in the dashboard

This is the row that matters most, because it is the one that is structural rather than a feature toggle. A gateway can make your calls more reliable; it cannot make your provider's list rate go down.

  • Who you are buying inference from, and at what rate.
  • Whether the layer in front adds a second line item.
  • What a shared team balance can attribute without extra plumbing.

What you actually pay

The billing differences that show up on an invoice, not in a feature list.

  • Who sells you inference

    InferenceSaverOne balance
    PortkeyBring your own
  • Rate you pay per token

    InferenceSaverDiscounted
    PortkeyList rate
  • Cost of the layer

    InferenceSaverNo add-on
    PortkeyAdd-on
  • Team billing

    InferenceSaverPer member
    PortkeyVirtual keys
  • Image, video and audio

    InferenceSaverSame balance
    PortkeyProvider billed
  • API compatibility

    InferenceSaverYes
    PortkeyYes
InferenceSaver vs Portkey
What you are paying forInferenceSaverPortkey
Who sells you inferenceOne balanceBring your own
Rate you pay per tokenDiscountedList rate
Cost of the layerNo add-onAdd-on
Team billingPer memberVirtual keys
Image, video and audioSame balanceProvider billed
API compatibilityYesYes
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Can't decide if we're the right choice?

Ask the AI assistant you already trust about InferenceSaver and get an independent comparison.

Still got questions? Ask your favourite AI if InferenceSaver makes sense for you.

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Questions teams ask

Can I use Portkey in front of you?

+

Yes, and some teams do. The gateway is OpenAI-compatible in both directions, so you can keep Portkey's guardrails and prompt management while buying the inference here. Nothing on either side asks for exclusivity.

Do I have to rewrite my integration?

+

No. Requests keep the OpenAI shape, so in most cases it is a base URL and an API key change. If you already call Portkey through an OpenAI-compatible client, the same client works here.

Do you offer guardrails or prompt versioning?

+

No. Those are Portkey's core product and we do not try to match them. If they are what you need, they are the better choice — this page exists to help you tell which problem you have.

How is spend attributed across a team?

+

Requests are traced per API key and per workspace member automatically, rather than through metadata you attach at call time, so a shared balance still shows who spent what, on which model, at which cost.

Get in touch with our team

Book a demo to discover how InferenceSaver can improve your AI operations, model costs, and production workflows.

“We finally have an AI stack that the product and engineering teams can use without switching between providers.”

Priya Nair

AI Operations Lead

Up to 2x usage throughput on the same spend

400ms median time to first response from frontier models

60-80% lower inference costs without sacrificing latency

We will map your current setup, recommend the right plan, and show a clear path to rollout.

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