AI · head to head
Helicone vs Kubeflow
Helicone
AI
Open-source LLM observability and gateway platform for AI applications
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Helicone the free Hobby plan is capped at 10,000 requests per month, which teams with production traffic can exceed quickly.; Kubeflow complex installation and configuration requiring Kubernetes expertise, upgrade paths between versions need manual CRD migrations
- They diverge on capability: Helicone covers Request dashboard and tracking, Kubeflow covers ML pipelines.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which Helicone and Kubeflow actually diverge.
Identical on both: starting price (Free), free tier (Yes), 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 Helicone
- Request dashboard and tracking
- Sessions and segments
- Helicone Query Language (HQL)
- Prompt datasets and improvement
- Playground
- Rate limits and alerts
Only in Kubeflow
- ML pipelines
- Training operators
- Model serving
- Jupyter notebooks
- Hyperparameter tuning
- Kubernetes
- TensorFlow
- PyTorch
What people use each for
The jobs each tool is most often brought in to do.
Helicone
- Monitoring cost and latency of production LLM applicationsnot Kubeflow
- Debugging multi-step agent sessionsnot Kubeflow
- Managing and iterating on prompts across a teamnot Kubeflow
- Routing requests across multiple LLM providersnot Kubeflow
Kubeflow
- Machine learningnot Helicone
- Data analysisnot Helicone
- Model trainingnot Helicone
- Predictive analyticsnot Helicone
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Helicone
- The free Hobby plan is capped at 10,000 requests per month, which teams with production traffic can exceed quickly.
- Advanced compliance features like SOC 2 and HIPAA are only available starting at the $799/month Team plan.
- Usage beyond the free tier is billed on top of the base subscription, adding cost unpredictability at scale.
- On-premises deployment is restricted to the custom Enterprise tier.
Kubeflow
- Complex installation and configuration requiring Kubernetes expertise, upgrade paths between versions need manual CRD migrations
- Resource-intensive infrastructure with minimal installs consuming significant CPU and memory
- Limited multi-tenancy support and multi-cloud setup leaves users largely on their own
- No native CI/CD integration, requiring custom glue code for versioning and automated deployments
- Debugging jobs and monitoring workloads often requires dropping down into raw Kubernetes commands
Pricing, plan by plan
Helicone
Free- HobbyFree
- 10,000 free requests
- 1 GB storage
- 1 seat
- Pro$79/month
- 10K free requests included, usage-based beyond
- 7-day free trial
- Unlimited playgrounds and workspaces
- Team$799/month
- 5 organizations
- SOC 2 and HIPAA compliance
- Dedicated Slack channel access
- Enterprise$undefined/mo
- Custom MSAs and SAML SSO
- On-premises deployment
- Bulk cloud discounts
Kubeflow
FreeNo published plan breakdown. See the Kubeflow review.
Which should you pick?
Choose Helicone if
- You need request dashboard and tracking.
- You want to start without paying.
- You work on web, api.
- You also want sessions and segments.
Choose Kubeflow if
- You need ml pipelines.
- You want to start without paying.
- You work on Kubernetes.
- You also want training operators.
Questions people ask
- Is Helicone or Kubeflow better?
- Neither clearly leads. Helicone starts at Free and Kubeflow at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Helicone or Kubeflow?
- Helicone starts at Free and Kubeflow at Free.
- Does Helicone or Kubeflow run on more platforms?
- Helicone runs on web, api. Kubeflow runs on Kubernetes.
- Can I use Helicone for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Helicone best used for?
- Helicone is most often used for monitoring cost and latency of production llm applications, debugging multi-step agent sessions, managing and iterating on prompts across a team, routing requests across multiple llm providers. Of those, monitoring cost and latency of production llm applications and debugging multi-step agent sessions are not what Kubeflow is typically brought in for.
- What can Helicone do that Kubeflow cannot?
- Helicone covers Request dashboard and tracking, Sessions and segments, Helicone Query Language (HQL), Prompt datasets and improvement. Kubeflow covers ML pipelines, Training operators, Model serving, Jupyter notebooks.
Answered from the vendors’ own pages
Helicone: What does Helicone cost?
Helicone offers a free Hobby plan, a Pro plan at $79/month, a Team plan at $799/month, and custom Enterprise pricing, with usage-based charges applying beyond included request limits.
SourceKubeflow: Is Kubeflow free to use?
Yes, Kubeflow is free and open-source under Apache License 2.0. However, you pay for the underlying Kubernetes infrastructure, which typically costs $500 to $5,000 per month depending on scale and cloud provider.
SourceHelicone: Is there a free plan, and what are its limits?
The free Hobby plan includes 10,000 requests per month, 1 GB of storage, 1 seat, and 1 organization, aimed at kickstarting AI projects.
SourceKubeflow: Do I need Kubernetes expertise to use Kubeflow?
Kubeflow requires significant Kubernetes and DevOps expertise. The installation deploys dozens of services and CRDs, often requiring manual configuration and troubleshooting. Data scientists typically need to convert scripts to containerized components.
SourceHelicone: Are there discounts available?
Helicone offers 50% off the first year for qualifying startups, discounts for non-profits, a $100 annual credit for open-source projects, and free access for students.
SourceKubeflow: What platforms can Kubeflow run on?
Kubeflow runs on any Kubernetes-compliant cluster, including on-premise, AWS, Azure, Google Cloud, and hybrid environments. This multi-cloud portability is one of its key advantages over managed alternatives.
SourceKubeflow: How does Kubeflow compare to managed services like SageMaker?
Kubeflow offers multi-cloud portability and lower long-term costs but requires more operational overhead. SageMaker provides a fully managed experience with better UI and less infrastructure work, but creates vendor lock-in to AWS.
SourceRelated pages
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