Machine Learning · head to head
JMP vs PromptLayer

JMP
Machine Learning
Desktop statistical and design of experiments software from a SAS subsidiary
- From
- Free
- Free plan
- Yes

PromptLayer
AI
Collaboration platform for prompt management, evaluation, and observability
- From
- Free
- Free plan
- Yes
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.; PromptLayer the free plan is capped at only 2,500 requests per month, quite limited for active production use.
- They diverge on capability: JMP covers Custom design of experiments, PromptLayer covers Visual prompt management.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which JMP and PromptLayer actually diverge.
| Attribute | JMP | PromptLayer |
|---|---|---|
| Pricing model | subscription | freemium |
| Platforms | Mac, Windows | web, api |
| Category | Machine Learning | AI |
| Founded | 1976 | Unknown |
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 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 PromptLayer
- Visual prompt management
- Agent observability
- Evaluations
- Version control
- Cost and latency monitoring
- Agent workflow tracing
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 PromptLayer
- Process capability and control chart work in a manufacturing quality function that has to produce evidence for a customer or regulatornot PromptLayer
- Exploratory analysis by an engineer or scientist who will not write code but needs more than a spreadsheetnot PromptLayer
- Semiconductor, chemical and pharmaceutical development groups where JMP is already the shared language for reporting resultsnot PromptLayer
PromptLayer
- Versioning and deploying prompts without code redeploysnot JMP
- Running evaluations with human review before production releasenot JMP
- Tracing multi-step agent workflows for debuggingnot JMP
- Monitoring LLM cost and latency by featurenot 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.
PromptLayer
- The free plan is capped at only 2,500 requests per month, quite limited for active production use.
- The Team plan jumps to $500/month, a large step up from the $49/month Pro plan.
- Overage transaction fees apply on top of subscription costs, which can make total spend less predictable.
- Enterprise-grade features like HIPAA BAAs and custom deployment require contacting sales.
Pricing, plan by plan
JMP
Free- TrialFree
- 30-day trial
- Full features
- JMP$1785/year
- Core JMP
- Standard features
PromptLayer
Free- FreeFree
- 5 users
- 2,500 requests/month
- 1 workspace
- Pro$49/month
- Unlimited playgrounds and workspaces
- 150MB datasets
- Pay-as-you-go overage at $0.003/transaction
- Team$500/month
- 25 users
- 100k+ monthly requests
- Webhooks
- Enterprise$undefined/mo
- Custom limits
- Role-based access controls
- HIPAA with BAA
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.
Choose PromptLayer if
- You need visual prompt management.
- You want to start without paying.
- You work on web, api.
- You also want agent observability.
Questions people ask
- Is JMP or PromptLayer better?
- Neither clearly leads. JMP starts at Free and PromptLayer at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, JMP or PromptLayer?
- JMP starts at Free and PromptLayer at Free.
- Does JMP or PromptLayer run on more platforms?
- JMP runs on Mac, Windows. PromptLayer runs on web, api.
- 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 PromptLayer is typically brought in for.
- What can JMP do that PromptLayer cannot?
- JMP covers Custom design of experiments, Linked interactive graphics, Analysis platforms, Quality and process tools. PromptLayer covers Visual prompt management, Agent observability, Evaluations, Version control.
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.
PromptLayer: What does PromptLayer cost?
PromptLayer has a free plan, a Pro plan at $49/month, a Team plan at $500/month, and custom Enterprise pricing, with additional usage billed per transaction beyond plan limits.
SourceJMP: 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.
PromptLayer: Is there a free plan, and what are its limits?
The Free plan includes 5 users, 2,500 requests per month, 1 workspace, 250 monthly eval cell executions, and datasets up to 10MB.
SourceJMP: Does it run on Linux?
No. Windows and macOS only, as an installed application.
PromptLayer: How is usage metered beyond the plan limits?
Additional usage is charged per transaction for requests, agent runs, and evaluation cell runs, at $0.003/transaction on Pro and $0.002/transaction on Team.
SourceJMP: 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.
Related pages
More on PromptLayer
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