Side-by-side comparison of Gemma 4 E4B Instruct (Google DeepMind · United States) and LFM2.5-8B-A1B (Liquid AI) for self-hosted deployment of the open-weight model. Gemma 4 E4B Instruct is rated conditional; LFM2.5-8B-A1B is conditional. They part ways on licence: Gemma 4 E4B Instruct is "Apache 2.0", LFM2.5-8B-A1B is "LFM Open License 1.0".
| Field | ||
|---|---|---|
| Summary | ||
| Verdict | Conditional Based on published licence terms, Gemma 4 E4B is an edge-optimised multimodal variant under pure Apache 2.0 with no prohibited-use carve-outs. Audio input (30s) and on-device deployment push GDPR biometric, AI Act emotion-recognition, and Art. 25 data-protection-by-design obligations entirely onto the integrator with no Google-side telemetry or kill-switch. | Conditional Per the published LFM Open License v1.0, Liquid AI's terms are Apache-2.0-derived but cap free commercial use at USD 10M annual company revenue — above that threshold deployers must negotiate a paid licence with [email protected]. The model itself is a strong 8.3B / 1.5B-active MoE built for CPU and edge inference, but the 38-trillion-token training corpus is undisclosed and Liquid AI is a US-based MIT spinoff, so EU regulated buyers should run their own DPIA and document the data-transfer story alongside any commercial-tier negotiation. |
| Last reviewed | 2026-04-17 | 2026-05-30 |
| Open-weight | ||
| Licence | Apache 2.0 | LFM Open License 1.0 |
| Commercial use | Unrestricted | Free under $10M revenue |
| Training data | Domain-level summary | Undisclosed |
| Origin | United States | USA (Boston) |
| Performance & pricing? | ||
| Quality index | 15/100 | — |
| Speed | — | — |
| Blended price | — | — |
| Context window | — | — |
| Evidence | ||
| Sources | ||
No overlapping sources between the two entries.