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Runpod vs Synexa

Two fact sheets from our own research, side by side — pricing, platforms, API access and status re-checked by us rather than quoted from the vendors.

The short answer

Free plan
Neither — Runpod has paid plans only, Synexa has paid plans only
Public API
Both have one
Best fit
Runpod: Developers fine-tuning or serving open models on a budget · Synexa: Developers running FLUX or SDXL image generation behind their own app
Trust score
About even — Runpod 72, Synexa 68
Status
Both up at our last check — Runpod Oct 29, 2026, Synexa Oct 16, 2026

From our own records as of each tool's last check. Anything we have not confirmed is left out rather than guessed. How we verify

RunpodPay-as-you-go GPU cloud for renting pods by the hour and running serverless inference endpoints that scale to zero.SynexaServerless API for running 100+ image, video, 3D and audio models, billed per output or per second of GPU time

Side by side

FactRunpodSynexa
CategoryGPU Cloud & ComputeModel Hosting & Inference
Pricing modelPaidPaid
Starts at—$0.0015/image
Public APIYesYes
Trust score72 / 10068 / 100
PlatformsWeb, APIWeb, API
CompanyRunpod Inc.—
Launched2022—
Last verifiedOct 29, 2026Oct 16, 2026

What our research says

Runpod

Runpod is a practical choice for indie developers, researchers and startups who want a GPU in minutes at a lower hourly rate than the hyperscalers. Teams with strict compliance needs should stick to Secure Cloud or a hyperscaler, and anyone forgetful about idle resources should watch storage charges.

Pros

  • Low hourly GPU rates with no commitment
  • Serverless endpoints scale down when idle
  • Wide range of GPUs from consumer cards to data-centre parts
  • API and templates for common AI stacks

Cons

  • Community Cloud runs on third-party hosts with variable availability
  • Storage keeps billing even when pods are stopped
  • Popular GPUs can be out of stock in a given region

Synexa

Synexa is a Replicate-shaped service with published per-second GPU rates that undercut the usual A100 pricing, and scale-to-zero means an idle project costs nothing. Per-run prices for the popular image models are listed openly, which makes cost modelling straightforward. The problem is provenance: the terms of service name no company, no jurisdiction and no address, which is a hard sell for anything beyond side projects.

Pros

  • Per-second GPU rates published openly, down to $0.000119 on a 3090
  • Flat per-run prices for the common image, video and 3D models
  • Scale-to-zero, so idle projects cost nothing
  • REST plus Python and JavaScript SDKs, with a single-POST run flow

Cons

  • No legal entity, address or country published anywhere, and the terms' governing-law clause still reads '[Jurisdiction]'
  • The 99.9% uptime and sub-100ms routing claims come with no status page evidence
  • Per-output price table omits the currency sign
  • An about page exists in the navigation but returns 404

Which one fits

Choose Runpod if you need

  • Developers fine-tuning or serving open models on a budget
  • Startups running bursty inference on serverless GPUs
  • Researchers who need a specific GPU for a few hours

Choose Synexa if you need

  • Developers running FLUX or SDXL image generation behind their own app
  • Bursty workloads that would waste money on a reserved GPU
  • Teams comparing per-run cost against Replicate or Fal

Runpod vs Synexa: the questions people ask

Is Runpod cheaper than Synexa?

Synexa starts at $0.0015/image. An entry price for Runpod is not confirmed by us yet, so check its pricing page before you compare.

Which has a public API, Runpod or Synexa?

Both ship a public API, so either can be built on; the fact table above shows the platforms each one runs on.

More comparisons

All Synexa alternatives →Browse all GPU Cloud & Compute →