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Machine Learning · head to head

JMP vs Ollama

JMP logo

JMP

Machine Learning

Desktop statistical and design of experiments software from a SAS subsidiary

From
Free
Rated
-
Full reviewWebsite
Ollama logo

Ollama

Machine Learning

Open-source tool for running LLMs locally on desktop and servers

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: 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.; Ollama requires user to provide computational hardware; no free cloud compute; models may not fit in available RAM on typical machines
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which JMP and Ollama actually diverge.

Attributes where JMP and Ollama differ
AttributeJMPOllama
Pricing modelsubscriptionfreemium
PlatformsMac, WindowsmacOS, Windows, Linux, Cloud (AWS, Google Cloud, Azure, self-hosted)
Founded1976Unknown

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Machine Learning).

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 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

Only in Ollama

Nothing recorded that JMP does not also cover.

What people use each for

The jobs each tool is most often brought in to do.

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 Ollama
  • Process capability and control chart work in a manufacturing quality function that has to produce evidence for a customer or regulatornot Ollama
  • Exploratory analysis by an engineer or scientist who will not write code but needs more than a spreadsheetnot Ollama
  • Semiconductor, chemical and pharmaceutical development groups where JMP is already the shared language for reporting resultsnot Ollama

Ollama

  • Local development and testing without API costs or rate limitsnot JMP
  • Privacy-sensitive applications requiring data to remain on-devicenot JMP
  • Cost-sensitive deployments where computational resources are already availablenot JMP
  • Fully offline environments or air-gapped networksnot JMP

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

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.

Ollama

  • Requires user to provide computational hardware; no free cloud compute; models may not fit in available RAM on typical machines
  • No hosted service option for inference; all computational burden falls to user
  • Limited to open-weight models; cannot run proprietary models like GPT-4 or Claude locally
  • Performance depends entirely on user's hardware; no SLAs or guarantees on speed

Pricing, plan by plan

JMP

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

Ollama

Free
  • FreeFree
    • CLI, API, desktop apps
    • Unlimited public models
    • 40,000+ community integrations
  • Pro$20/month
    • Access to larger, more powerful cloud models
    • Run 3 concurrent cloud models
    • 50x more usage than Free
  • Max$100/month
    • Run 10 concurrent cloud models
    • 5x more usage than Pro
  • Team$25/month
    • Per seat pricing (5-seat minimum = $125/month)
    • Shared billing
    • Zero data retention

Which should you pick?

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

Choose Ollama if

  • You want to start without paying.
  • You work on macOS, Windows, Linux, Cloud (AWS, Google Cloud, Azure, self-hosted).
Ollama review

Questions people ask

Is JMP or Ollama better?
Neither clearly leads. JMP starts at Free and Ollama at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, JMP or Ollama?
JMP starts at Free and Ollama at Free.
Does JMP or Ollama run on more platforms?
JMP runs on Mac, Windows. Ollama runs on macOS, Windows, Linux, Cloud (AWS, Google Cloud, Azure, self-hosted).
Can I use JMP for free?
Both have a free tier, so you can try either at no cost before committing.
What is JMP best used for?
JMP is most often used for 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 have, process capability and control chart work in a manufacturing quality function that has to produce evidence for a customer or regulator, exploratory analysis by an engineer or scientist who will not write code but needs more than a spreadsheet, semiconductor, chemical and pharmaceutical development groups where jmp is already the shared language for reporting results. Of those, 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 have and process capability and control chart work in a manufacturing quality function that has to produce evidence for a customer or regulator are not what Ollama is typically brought in for.
What can JMP do that Ollama cannot?
JMP covers Custom design of experiments, Linked interactive graphics, Analysis platforms, Quality and process tools.

Answered from the vendors’ own pages

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.

Ollama: How much does Ollama cost?

Ollama is free to use with unlimited public models. Pro paid plans start at $20/month for 3 concurrent cloud models, or $100/month for Max with 10 concurrent models. Team plans cost $25/seat/month with a 5-seat minimum.

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.

Ollama: What does the Ollama free tier include?

The free tier includes CLI and API access, unlimited public models, 40,000+ community integrations, and private data retention, though limited to 1 concurrent cloud model.

Source
JMP: Does it run on Linux?

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

Ollama: How much usage is included with each Ollama plan?

Pro includes 50x more usage than Free, and Max includes 5x more usage than Pro. Session limits reset every 5 hours and weekly limits reset every 7 days across all tiers.

Source
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.

Ollama: Does Ollama log or train on user data?

No, Ollama explicitly states that prompt or response data is never logged or trained on, protecting user privacy across all plans.

Source
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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