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Machine Learning · head to head

JMP vs Tabnine

JMP logo

JMP

Machine Learning

Desktop statistical and design of experiments software from a SAS subsidiary

From
Free
Free plan
Yes
Full reviewWebsite
Tabnine logo

Tabnine

AI

AI coding agents built for enterprise privacy and control

From
$39/month
Free plan
No
Full reviewWebsite

The short version

  • Only JMP has a free tier, so it costs nothing to try first.
  • 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.; Tabnine no published free tier as of the current pricing page, unlike several competitors that offer free individual plans
  • They diverge on capability: JMP covers Custom design of experiments, Tabnine covers Code Completions.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which JMP and Tabnine actually diverge.

Attributes where JMP and Tabnine differ
AttributeJMPTabnine
Starting priceFree$39/month
Free tierYesNo
PlatformsMac, Windowswindows, mac, linux, web
CategoryMachine LearningAI
Founded19762017

Identical on both: pricing model (subscription), 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 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 Tabnine

  • Code Completions
  • AI Chat
  • Agentic Workflows
  • Context Engine
  • Zero Code Retention
  • Flexible Deployment
  • Codebase Integrations

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

Tabnine

  • Enterprise teams requiring on-premises or air-gapped AI coding toolsnot JMP
  • Organizations with strict IP and data privacy requirementsnot JMP
  • Teams wanting codebase-aware code completionsnot JMP
  • Regulated industries needing compliance-certified AI toolingnot 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.

Tabnine

  • No published free tier as of the current pricing page, unlike several competitors that offer free individual plans
  • Pricing is higher than many consumer-focused AI coding assistants, targeting enterprise budgets
  • Now owned by Tricentis, a testing-focused company, introducing uncertainty about long-term product direction outside quality engineering use cases
  • LLM usage costs apply separately when using Tabnine-provided model access, on top of the per-seat license fee

Pricing, plan by plan

JMP

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

Tabnine

$39/month
  • Code Assistant Platform$39/month
    • AI code completions
    • AI chat across the SDLC
    • Works with all major IDEs
  • Agentic Platform$59/month
    • Everything in Code Assistant Platform
    • Autonomous coding agents
    • Customizable coaching guidelines

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 Tabnine if

  • You need code completions.
  • You work on windows, mac, linux, web.
  • You also want ai chat.
Tabnine review

Questions people ask

Is JMP or Tabnine better?
Neither clearly leads. JMP starts at Free and Tabnine at $39/month, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, JMP or Tabnine?
JMP has a free tier; the other does not. Paid plans start at Free for JMP and $39/month for Tabnine.
Does JMP or Tabnine run on more platforms?
JMP runs on Mac, Windows. Tabnine runs on windows, mac, linux, web.
Can I use JMP for free?
Yes. JMP has a free tier, so you can try it without paying. Tabnine starts at $39/month.
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 Tabnine is typically brought in for.
What can JMP do that Tabnine cannot?
JMP covers Custom design of experiments, Linked interactive graphics, Analysis platforms, Quality and process tools. Tabnine covers Code Completions, AI Chat, Agentic Workflows, Context Engine.

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.

Tabnine: What does Tabnine cost?

The Code Assistant Platform is $39/user/month and the Agentic Platform, which adds autonomous agents and the CLI, is $59/user/month, both billed as annual subscriptions.

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.

Tabnine: Is there a free plan?

Tabnine's pricing page does not list a permanent free tier; both published plans are paid per-seat subscriptions aimed at professional and enterprise teams.

Source
JMP: Does it run on Linux?

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

Tabnine: Does Tabnine charge extra for LLM usage?

Usage is unlimited when connecting your own on-prem or cloud LLM endpoint, but additional fees apply when using Tabnine-provided model access on top of the seat license.

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.

Tabnine: What deployment options does Tabnine support?

Tabnine can be deployed as SaaS, in a private VPC, fully on-premises, or in a completely air-gapped environment to meet enterprise data-control requirements.

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.

Tabnine: What is included in the Agentic Platform tier?

It adds autonomous coding agents with optional human oversight, the Tabnine CLI, the Context Engine, MCP integration, and unlimited codebase connections beyond the base Code Assistant plan.

Source
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