Groq vs Liquid AI
A side-by-side comparison of Groq and Liquid AI, two Inference tools, drawn from Ignaite's continuously-verified listings.
Compared from listings verified as of
Liquid AI
InferenceOn-device foundation models (LFMs) plus LEAP, an edge platform to ship them to any device.
View Liquid AIAt a glance
| Attribute | Groq | Liquid AI |
|---|---|---|
| Category | Inference | Inference |
| Pricing | FREEMIUM | FREEMIUM |
| License | Proprietary | Proprietary |
| Deployment (differs) | Cloud | Hybrid |
| Platforms (differs) | API, Web | Web, iOS, Android, API |
| Model support (differs) | Multi-model | Self-contained (on-device) |
| Vendor (differs) | Groq | Liquid AI |
The honest brief
Groq
Custom LPU silicon delivers deterministic sub-100ms TTFT, ideal for voice and latency-critical apps.
- Hundreds of tokens/sec on open models
- Sub-100ms time-to-first-token
- Deterministic, low-variance latency
- OpenAI-compatible API with free tier
- Curated open-weight models only
- No frontier closed models (GPT/Claude)
- SRAM limits large context windows
- Rate limits during peak demand
Liquid AI
Runs capable LLMs fully on-device — no cloud, low latency, private — via compact LFMs you can fine-tune and ship with one Edge SDK.
- Runs on phones, laptops, edge hardware
- Compact 350M–8.3B LFM2/LFM2.5 family
- LEAP core is free for all users
- Discover, bundle, deploy via Edge SDK
- Open-weight models
- Small models trail frontier cloud LLMs
- On-device deployment adds app work
- Enterprise support is sales-gated
- Custom (non-OSI) model license