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AI · head to head

Helicone vs JMP

Helicone logo

Helicone

AI

Open-source LLM observability and gateway platform for AI applications

From
Free
Free plan
Yes
Full reviewWebsite
JMP logo

JMP

Machine Learning

Desktop statistical and design of experiments software from a SAS subsidiary

From
Free
Free plan
Yes
Full reviewWebsite

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.; JMP it is a desktop application holding the working table in memory, so a data set that outgrows the workstation has no in-place upgrade path, only a move to a different tool and a different skill set.
  • They diverge on capability: Helicone covers Request dashboard and tracking, JMP covers Custom design of experiments.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Helicone and JMP actually diverge.

Attributes where Helicone and JMP differ
AttributeHeliconeJMP
Pricing modelfreemiumsubscription
Platformsweb, apiMac, Windows
CategoryAIMachine Learning
FoundedUnknown1976

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 JMP

  • Custom design of experiments
  • Linked interactive graphics
  • Analysis platforms
  • Quality and process tools
  • Graph Builder
  • JSL scripting
  • Scoring code export
  • Predictive modelling in JMP Pro

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 JMP
  • Debugging multi-step agent sessionsnot JMP
  • Managing and iterating on prompts across a teamnot JMP
  • Routing requests across multiple LLM providersnot JMP

JMP

  • Planning a physical experiment where each run is expensive, and the question is which twelve runs to perform rather than how to model data you already havenot Helicone
  • Process capability and control chart work in a manufacturing quality function that has to produce evidence for a customer or regulatornot Helicone
  • Exploratory analysis by an engineer or scientist who will not write code but needs more than a spreadsheetnot Helicone
  • Semiconductor, chemical and pharmaceutical development groups where JMP is already the shared language for reporting resultsnot 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.

JMP

  • It is a desktop application holding the working table in memory, so a data set that outgrows the workstation has no in-place upgrade path, only a move to a different tool and a different skill set.
  • There is no Linux build and no server edition for running analyses, so JMP cannot sit in a scheduled pipeline the way an R or Python script can, and recurring reports depend on a named person running them on a laptop.
  • The predictive modelling capability most buyers mean when they call this machine learning software is in JMP Pro, a separate and more expensive licence, so the base product's price is not the price of the thing being evaluated.
  • JSL is proprietary to JMP, so the scripts, add-ins and automation a group accumulates over a decade do not port anywhere and become sunk cost the moment anyone questions the renewal.
  • Deployment ends at exported scoring code with no registry, monitoring or retraining, so a model that runs in production is maintained by another team in another language and steadily diverges from the version the analyst still has open.

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

JMP

Free
  • TrialFree
    • 30-day trial
    • Full features
  • JMP$1785/year
    • Core JMP
    • Standard features

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.
Helicone review

Choose JMP if

  • You need custom design of experiments.
  • You want to start without paying.
  • You work on Mac, Windows.
  • You also want linked interactive graphics.
JMP review

Questions people ask

Is Helicone or JMP better?
Neither clearly leads. Helicone starts at Free and JMP at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Helicone or JMP?
Helicone starts at Free and JMP at Free.
Does Helicone or JMP run on more platforms?
Helicone runs on web, api. JMP runs on Mac, Windows.
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 JMP is typically brought in for.
What can Helicone do that JMP cannot?
Helicone covers Request dashboard and tracking, Sessions and segments, Helicone Query Language (HQL), Prompt datasets and improvement. JMP covers Custom design of experiments, Linked interactive graphics, Analysis platforms, Quality and process tools.

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.

Source
JMP: Is JMP the same thing as SAS?

No. JMP is a separate desktop product from a SAS subsidiary, with its own interface, its own scripting language and its own licence. Knowing SAS does not transfer to it beyond the statistics.

Helicone: 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.

Source
JMP: Do I need JMP Pro?

If you want cross validation, penalised regression, boosted trees or neural networks, yes. The base edition covers classical statistics, graphics and design of experiments well and stops short of predictive modelling.

Helicone: 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.

Source
JMP: Does it run on Linux?

No. Windows and macOS only, as an installed application.

JMP: Can I put a JMP model into production?

Only by exporting the scoring formula as SQL, C, Python or similar and running it in another system. JMP itself does not serve, monitor or retrain models.

JMP: Who actually uses it?

Process and quality engineers, and scientists in R&D, particularly in semiconductor, chemicals, pharmaceutical and medical device work. It is not usually chosen by data engineering or platform teams.

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