LMQL vs Private LLM

Side-by-side comparison · Updated April 2026

 LMQLLMQLPrivate LLMPrivate LLM
DescriptionLMQL is a programming language tailored for large language models (LLMs). It offers robust and modular LLM prompting through the use of types, templates, constraints, and an optimizing runtime. It simplifies the creation of complex prompts by allowing procedural programming techniques in a query-like syntax. Created by the SRI Lab at ETH Zurich, LMQL supports features such as nested queries, scripted prompting, and custom constraints. It also provides a Playground IDE for ease of use.Private LLM is an offline AI chatbot designed for iOS and macOS devices, ensuring user privacy and data security. It offers advanced text generation features using the latest AI models, all of which run locally on the user’s device. Users pay a one-time fee with no subscription required, enjoying seamless integration with Apple ecosystems, including Siri and Shortcuts. The app supports a wide range of open-source LLM models and employs cutting-edge quantization techniques to maintain high performance.
CategoryOtherAI Assistant
RatingNo reviewsNo reviews
PricingN/APaid
Starting PriceN/A$9.99/mo
Plans
  • Private LLM One-Time Purchase$9.99/mo
Use Cases
  • Developers
  • Researchers
  • Data Scientists
  • AI Practitioners
  • Privacy-conscious users
  • Apple ecosystem users
  • Students
  • Professionals
Tags
programming languagelarge language modelstypestemplatesconstraints
offlineAI chatbotiOSmacOSuser privacy
Features
Nested Queries
Scripted Prompting
Custom Constraints
Optimizing Runtime
Playground IDE
Local Model Support
Tool Augmentation
High-level Constraint Management
Sequential Query Execution
Integration with Popular Libraries
Offline functionality
Advanced model quantization with OmniQuant
Integration with Siri and Shortcuts
One-time purchase with no subscription
Wide range of open-source model support
Fully on-device data processing
High-performance text generation
Compatibility with multiple Apple devices
Privacy-first design
User-friendly interface
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