Liquid AI vs Ollama
A side-by-side look at scores, pricing and features — with RECATOOLS' ASEAN-aware verdict for each.
Liquid AI
Non-Transformer AI models built for efficient on-device inference
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Ollama
Run open-weights LLMs locally on your own machine
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| RECATOOLS Score | 7.8 / 10 | 8.8 / 10 |
| Capability | ||
| Value for money | ||
| Ease of use | ||
| ASEAN readiness | ||
| API quality | ||
| Pricing | Freemium | Open Source |
| Free tier | Free weights via Hugging Face; Playground access; LEAP SDK; Liquid Apollo app | — |
| Paid from | Custom enterprise pricing (contact sales); some models served via OpenRouter | — |
| Has API | ✓ | ✓ |
| Open source | ✗ | ✓ |
| Free to use | ✓ | ✓ |
| Users | Early enterprise and developer adoption; customer base not publicly disclosed | — |
| Founded | 2023 | 2023 |
| Maker | Liquid AI (independent) | — |
| Verdict | Liquid AI's bet is architectural: skip Transformers, build on liquid neural networks instead, and win on efficiency rather than raw scale. The numbers back it up so far — LFM2 claims 200% higher CPU throughput than Qwen3... |
Ollama is the de facto easiest way to run open-weight LLMs locally — a single command pulls and serves models like Llama, Mistral, Qwen and Gemma, with an OpenAI-compatible API and growing GUI. It has become foundational... |
| Full review → | Full review → |
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Comparisons cover up to 4 tools. Scores are RECATOOLS editorial assessments; verify current pricing on each vendor's site.