Side-by-side comparison of LFM2.5-8B-A1B (Liquid AI) and Talkie-1930-13B Base (Talkie-LM (research)) for self-hosted deployment of the open-weight model. LFM2.5-8B-A1B is rated conditional; Talkie-1930-13B Base is conditional. They part ways on licence: LFM2.5-8B-A1B is "LFM Open License 1.0", Talkie-1930-13B Base is "Apache 2.0".
| Field | ||
|---|---|---|
| Summary | ||
| Verdict | 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. | Conditional Per the published model card, Talkie-1930-13B Base is the pretrained sibling of the Talkie-1930 instruction-tuned release: an Apache 2.0 13B model trained on 260B tokens of pre-1931 English text drawn entirely from public-domain sources. Training-data transparency is unusually clean for AI Act Article 53 purposes; the limits are vendor jurisdiction (a US-affiliated research collaboration with no published EU DPA) and the deliberate vintage corpus, which makes the model unsuitable for any task requiring post-1931 factual knowledge. |
| Last reviewed | 2026-05-30 | 2026-05-03 |
| Open-weight | ||
| Licence | LFM Open License 1.0 | Apache 2.0 |
| Commercial use | Free under $10M revenue | Unrestricted |
| Training data | Undisclosed | Documented |
| Origin | USA (Boston) | US (research) |
| Performance & pricing? | ||
| Quality index | — | — |
| Speed | — | — |
| Blended price | — | — |
| Context window | — | — |
| Evidence | ||
| Sources | ||
No overlapping sources between the two entries.