Machine Learning & Data Science · head to head
Groq vs Seldon
Groq
Machine Learning & Data Science
Fast inference provider using proprietary LPU hardware for low-latency serving
- From
- On request
- Rated
- -
Seldon
Machine Learning & Data Science
Deploy, scale, and monitor machine learning models
- From
- Free
- Rated
- -
The short version
- Only Seldon has a free tier, so it costs nothing to try first.
- Each has a real cost: Groq pricing is not published and is sold entirely by quote, making cost comparison difficult; Seldon production deployment requires a Kubernetes cluster, whether managed such as GKE, EKS or AKS, or on-premises such as OpenShift
Where they differ
Only the attributes on which Groq and Seldon actually diverge.
Identical on both: user rating (Not yet rated), category (Machine Learning & Data Science).
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 Groq
Nothing recorded that Seldon does not also cover.
Only in Seldon
- Model serving
- A/B testing
- Canary deployments
- Outlier detection
- Model explainability
- Kubernetes
- Istio
- Prometheus
What people use each for
The jobs each tool is most often brought in to do.
Groq
- Latency-sensitive applications requiring sub-second inference response timesnot Seldon
- High-volume inference workloads where cost per inference matters at scalenot Seldon
- Custom model deployment with performance guaranteesnot Seldon
- Enterprise applications seeking inference-specific infrastructurenot Seldon
Seldon
- Serving and routing machine learning models on Kubernetesnot Groq
- Building multi-step inference pipelines with A/B tests and explainersnot Groq
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Groq
- Pricing is not published and is sold entirely by quote, making cost comparison difficult
- Limited to open-weight models; no proprietary model access through the platform
- Not widely integrated into third-party AI platforms compared to OpenAI or Anthropic
Seldon
- Production deployment requires a Kubernetes cluster, whether managed such as GKE, EKS or AKS, or on-premises such as OpenShift
- The documented components carry both minimum and maximum supported versions, so newer Kubernetes and dependency versions are not automatically supported
- Dataflow Pipelines need an additional component that the docs recommend avoiding installing when pipelines are not used
- The Docker Compose install is offered as a lightweight alternative for environments without Kubernetes rather than as a production path
Pricing, plan by plan
Groq
On requestNo published plan breakdown. See the Groq review.
Seldon
Free- Seldon CoreFree
- Open source
- Kubernetes deployment
- Model serving
- Seldon DeployFree
- Enterprise features
- GUI
- Monitoring
Which should you pick?
Choose Seldon if
- You need model serving.
- You want to start without paying.
- You work on Linux.
- You also want a/b testing.
Questions people ask
- Is Groq or Seldon better?
- Neither clearly leads. Groq starts at On request and Seldon at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Groq or Seldon?
- Seldon has a free tier; the other does not. Paid plans start at On request for Groq and Free for Seldon.
- Does Groq or Seldon run on more platforms?
- Groq runs on API, Cloud. Seldon runs on Linux.
- Can I use Seldon for free?
- Yes. Seldon has a free tier, so you can try it without paying. Groq starts at On request.
- What is Groq best used for?
- Groq is most often used for latency-sensitive applications requiring sub-second inference response times, high-volume inference workloads where cost per inference matters at scale, custom model deployment with performance guarantees, enterprise applications seeking inference-specific infrastructure. Of those, latency-sensitive applications requiring sub-second inference response times and high-volume inference workloads where cost per inference matters at scale are not what Seldon is typically brought in for.
- What can Groq do that Seldon cannot?
- Seldon covers Model serving, A/B testing, Canary deployments, Outlier detection.