LMQL vs PromptBase: 2026 comparison

LMQL and PromptBase in brief

LMQL and PromptBase both help you work with instructions for language models, but they address different parts of that work. LMQL lets you write queries, constrain generated responses and inspect generation steps. PromptBase lets you search for, buy, sell and run prompts. The first supports programming and direct control over a generation process. The second connects a task with instructions offered by creators, through individual purchases or a paid subscription. Your starting point matters more than their shared developer tools category.

LMQL : LMQL lets developers write queries for language models and impose constraints on generated responses. It provides a visual environment for testing programs and inspecting the steps of generation.

PromptBase : PromptBase serves people searching for, buying, or selling prompts by model and use case. It also lets users run prompts with generation credits and commission custom work from creators.

They are often weighed against each other by people who hesitate. This page lines up their features point by point (10 criteria), with no partnership with either publisher.

Comparison table

Criterion by criterion

For each criterion: why it matters, each one's value and who has the edge. A criterion without data on both sides is not decided.

Free tier

A free tier lets you test the tool on your own examples before paying anything. LMQL : yes. PromptBase : yes. A tie on this point.

Entry price

The first paid plan, per month, gives the minimum cost of regular use; higher plans cost more. LMQL : not published. PromptBase : $14 per month. Cannot be decided: data missing on one side.

Public API

An API lets you connect the tool to your software, an automation tool or an AI agent. LMQL : yes. PromptBase : yes. A tie on this point.

Data export

Being able to get your content back avoids lock-in the day you want to switch tools. LMQL : yes. PromptBase : yes. A tie on this point.

Data hosting

Where data is stored matters for GDPR and client data: the EU or local processing make compliance simpler. LMQL : on device. PromptBase : not disclosed. Edge: LMQL.

Interface languages

More interface languages make the tool easier to roll out across an international team. LMQL : 1. PromptBase : 1. A tie on this point.

Platforms

The more platforms (web, desktop, mobile, extension), the better the tool fits your daily routine. LMQL : web browser, Linux, macOS, and Windows. PromptBase : web browser and API. Edge: LMQL.

Open source

Public code lets you audit the tool, self-host it and keep using it if the publisher changes course. LMQL : yes. PromptBase : no. Edge: LMQL.

Track record

A tool launched several years ago has a longer history: less risk of sudden shutdown, more user feedback. LMQL : launched in 2023. PromptBase : launched in 2022. Edge: PromptBase.

Recognition

The number of reference community lists citing the tool shows how well known it is among practitioners. LMQL : cited in 2 lists. PromptBase : cited in 2 lists. A tie on this point.

In charts

Our analysis

Released in 2023 by ETH Zurich, LMQL treats language model queries as part of a program. You can define constraints, test programs visually and inspect how generation proceeds. That approach suits developers who want to understand and refine the behavior of their queries. PromptBase, launched in 2022, follows a marketplace approach. You search by model and use case, purchase or sell prompts, and commission custom work from a creator. Its focus is access to instructions rather than building a constrained query program. Neither approach establishes better results by itself; each places a different part of the work in your hands.

LMQL is open source and has a free offering, while its entry price is not published in the supplied information. PromptBase uses a freemium model. Its Select plan costs 14 USD per month when billed annually, or 19 USD with monthly payment. Individual prompt purchases are also available. These are different ways of accessing the products, so the listed subscription prices alone do not describe every possible cost. LMQL scores 81 and PromptBase 61 for access and transparency. Those figures do not measure output quality. The supplied records also do not specify the detailed allowances of either free offering.

LMQL has open source code and lists local data hosting. It can nevertheless connect to local models or remote services, so the model you select still matters when considering where information goes. Its listed exports cover Playground session state and code capture. PromptBase is closed source, and its hosting location is not declared in the supplied record. Prompt text can be exported through its MCP server. These facts help you assess technical openness and what you can retrieve. They do not establish detailed confidentiality guarantees, retention rules or the handling of every request made through either tool in practice.

LMQL is listed for the web, Linux, macOS and Windows, with an API for integration. Its visual testing environment and generation inspection support repeated adjustments to queries. That makes sense when programming and testing are part of your intended workflow. PromptBase is available through the web and an API, and supports running prompts with generation credits. Its everyday usefulness depends on whether available prompts match your actual task. Neither product lists a French interface; each lists one interface language. The supplied information contains no shared task evaluation, so it cannot support a direct comparison of speed, reliability or response quality.

Depending on your situation

The right choice depends on use. For a few common situations, here are the criteria that matter and who wins (LMQL value / PromptBase value).

Personal use on a tight budget

Neither stands out on the criteria for this situation (free tier (yes / yes), entry price (not published / $14 per month), and interface languages (1 / 1)): decide with a trial.

Business use with client data

Neither stands out on the criteria for this situation (data hosting (on device / not disclosed), data export (yes / yes), and track record (launched in 2023 / launched in 2022)): decide with a trial.

Integration with your software

Here, LMQL has the edge: it wins 2 of the 3 criteria that matter in this situation, namely public api (yes / yes), open source (yes / no), and platforms (web browser, Linux, macOS, and Windows / web browser and API).

Which one to choose?

Choose LMQL if…

• you value data hosting (on device)
• you value platforms (web browser, Linux, macOS, and Windows)
• you value open source (yes)

Choose LMQL if you want to develop constrained queries and inspect how a language model generates its response. Open source code and support for local models also make it relevant when you want more technical control. It is a logical fit when you are prepared to write, test and maintain the programs behind your prompts.

Choose PromptBase if…

• you value track record (launched in 2022)

PromptBase fits users who want to find prompts by model or task, purchase an individual prompt, or request custom work from a creator. It also serves people who want to sell their own prompts. Before choosing a subscription, consider how that plan, individual purchases and generation credits relate to the way you expect to use it.

Strengths and limits of each

LMQL

• + Free tier to try it
• + Public API
• + Public source code

PromptBase

• + Free tier to try it
• + Cheaper than its category median
• + Public API
• − Data hosting not disclosed

The best test is still yours: take three real tasks from your day and give them to both for a week.

What about the others?

If neither suits you, look at Firecrawl, Keploy, Jina Reader, Metorial, Mintlify, and Metatron.

Related comparisons:

• LMQL vs Mintlify
• Mintlify vs PromptBase

Conclusion

The deciding factor is whether you want to build query behavior or obtain prompts for a task. LMQL provides an open programming framework with constraints and generation inspection. PromptBase provides a marketplace and access to creators, with several payment routes. LMQL is the more direct match for developing your own query logic. PromptBase is relevant when finding suitable instructions is your main need, subject to what its catalogue offers.