Artificial Intelligence · 11.08.2026, 20:10 UTC
webAI Releases TwIL-LM: A 1.7B and 3B Formal-Logic Model Family for Autoformalization on Local Hardware
| Schweregrad | info |
|---|---|
| Kategorie | Artificial Intelligence |
| Quelle | MarkTechPost ↗ |
| Veröffentlicht | 11.08.2026 UTC |
Sicherheitsmeldung mit Schweregrad noch nicht bewertet. Technische Details im Tab „Originaltext“; empfohlene Schritte in der Checkliste.
webAI has released TwIL-LM, a two-model family of formal-logic reasoners at 1.7B and 3B parameters. The 3B member, TwIL-LM3, is a merged fine-tune of SmolLM3-3B; the 1.7B member is a PEFT LoRA adapter for SmolLM2-1.7B-Instruct. Both target autoformalization: translating English into first-order logic and checking whether a conclusion follows from its premises. Both run locally, with a 1.06 GB quantized build for the 1.7B and a 1.78 GiB Q4_K_M GGUF for the 3B. webAI’s announcement frames the release around beating gpt-oss-120b on four of five formal-reasoning lanes.
Is it deployable?
Partially. Non-commercial use only, as of now.
Both checkpoints ship under the webAI Non-Commercial License ver. 1.0. Revenue-generating deployment requires a separate agreement with webAI.
Company level: any size. The 3B Q4_K_M GGUF is 1.78 GiB and runs on CPU or 4 GB of VRAM. The 1.7B Q4_K_M is 1.06 GB.
Industries: compliance and RegTech, financial services, healthcare and pharma, legal and contract operations, formal-methods research. webAI positions local execution for environments where data cannot leave the device.
Applications: first-order logic (FOL) translation, entailment classification over premise sets, natural language to structured query, Lean formalization drafting and critique, and a verifier layer that checks a larger model’s output.
How TwIL-LM3 was built?
Four stages sit on top of the base model. LoRA supervised fine-tuning on a synthetic formal-logic corpus. Checkpoint fusion, averaging intermediate SFT checkpoints in parameter space. WiSE-FT interpolation back …