webAI releases TwiL-LM, a family of formal-logic models that outreason a 120B model and run on an iphone. August 7, 2026 Built for compliance rules, contract logic, and research reasoning, the 3B model beats OpenAI's open-weights gpt-oss-120b, a model 40x its size, on four of five formal-reasoning benchmarks, while the 1-gigabyte 1.7B variant outperforms every sub-2B model webAI evaluated. [AUSTIN, Texas] - August 10, 2026 webAI today released TwiL-LM (Thinking webAI Intelligence Lab Language Model), a family of small formal-logic models at 1.7 billion and 3 billion parameters that run entirely on consumer hardware and outscore far larger models at deductive reasoning. TwiL-LM3, the 3B model, beats gpt-oss-120b, a model 40 times its size, on four of five benchmarks in webAI's formal-reasoning suite. Both models are available now on Hugging Face. TwiL-LM does one hard thing exceptionally well: it translates plain English into formal logic, checks whether conclusions follow from their premises, and works through multi-step deductive reasoning which is the backbone of compliance rules, contract conditions, research, and everyday decision-making. This is a contribution to the sub-field known as autoformalization. The AI-reasoning race has so far been a story about scale, with frontier labs pursuing better reasoning through ever-larger models served from data centers. TwiL takes the opposite bet: pure deductive reasoning, distilled into a package small enough to download onto a phone at about one gigabyte to connect with your non-internet data sources. It is an expert an enterprise can own and run at the edge instead of renting through an API. "What's surprised me most about TwiL is how useful it is beyond any single benchmark," said David Stout, CEO and co-founder of webAI. "I use it every day for writing, tool calling, and general reasoning, but the more interesting capability is how well it works alongside other expert models. TwiL can act almost like an auto-correct for AI - checking outputs, refining reasoning, enforcing structure, and helping specialized models produce better answers. And because it runs at around 300 tokens per second on an M2 MacBook, you can use that reasoning layer continuously without slowing everything else down." The numbers Against gpt-oss-120b on webAI's formal-reasoning suite, TwiL-LM3 (3B) scores: * 96.4 vs. 65.2 on rule induction (deriving rules from data) * 87.6 vs. 43.3 on semantic parsing (language into structured queries (token F1) * 64.6 vs. 63.1 on Lean formalization (theorem statements into formal code (token F1)) * 52.0 vs. 7.0 on exact-format answering: a 7.4x gap * 68.7 vs. 77.5 on entailment labeling (the one lane the 120B model keeps a lead) Beyond the formal-reasoning suite, TwiL-LM3 stays within striking distance of models many times its size on general benchmarks such as LogicBench (71.7) and GSM8K (87.3). In webAI's throughput tests it answered 2.6x faster than gpt-oss-120b, at 32.9 vs. 12.6 answers per second. The 1.7B variant, built for phones, roughly doubles its base model (0.361 vs. 0.185 aggregate reasoning accuracy over SmolLM2-1.7B) and led every sub-2B model webAI evaluated, outscoring Phi-4-mini, SmolLM-3B, Qwen2.5-3B, and Llama-3.2-3B, models in the 3-to-4-billion-parameter class. Expertise, not scale TwiL-LM1.7B's performance was driven by a proprietary reasoning data engine built from open sources and targeted fine-tuning from a 289 MB LoRA adapter of roughly 72 million parameters. The release is the continued public demonstration of webAI's collaborative intelligence thesis: that the future of AI is not one giant generalist rented through an API, but specialized AI models as experts that teams build and run themselves. "In the quest for artificial general intelligence (AGI) I think we are relearning the importance of narrow, specialized models that capture true expertise," said Dr. Paul J. Maykish, Chief Intelligence Officer, webAI. "A minor consensus is growing that real work gets done by teams of specific AI models that interact and improve with your non-internet, expert data. TwiL-LM1.7B is what one of those deductive-reasoning experts looks like - in a form that downloads at 1.06 GB onto your phone. We imagine that many specialized expert models combining on a network without the need for special silicon is one path to AGI." Built to run where the work happens The recommended quantized build is a 1.06 GB download that ran at roughly 367 tokens per second in webAI's evaluation, fast enough for a small laptop or a phone. Nothing is sent to an external cloud, which matters for regulated environments in healthcare, financial services, and pharmaceuticals where data cannot leave the device. Additional results include 0.655 on "entailment labeling" (checking if statements follow logically), the model's strongest objective, and 0.590 on the held-out LogicBench (a test for logic puzzles) against 0.563 for the base model. The model has an 8,192-token context window. For high-stakes formal work, webAI recommends pairing TwiL-LM with verification tooling such as a symbolic solver to benefit from the speed but account for the shorter context window. The 3B model has a longer ~65k-token context window for use cases where a standalone model is the best solution. Availability TwiL-LM 1.7B and 3B variants are available now on Hugging Face, in formats for both the Transformers ecosystem and local llama.cpp deployment, under the webAI Non-Commercial License v1.0. About webAI webAI is the enterprise AI platform that brings AI to your data. Built for mission-critical environments, it enables organizations to build and operate private, custom models with complete data sovereignty, real-time performance, and predictable economics. Media Contact [email protected]

webAI adds ŌURA CEO Tom Hale to board as privacy-focused AI strategy gains momentum. May 11, 2026 AI infrastructure company webAI has appointed ŌURA CEO Tom Hale to its board of directors, adding a veteran technology executive as the company expands its push into what it describes as "sovereign AI" - artificial intelligence systems designed around privacy, localized deployment and user-controlled data. The appointment reflects growing industry focus on AI architectures that keep data closer to users and organizations rather than relying entirely on centralized cloud models. webAI said Hale's experience scaling consumer technology and subscription platforms will help guide the company as it develops AI systems for mission-critical environments where privacy, control and trust are essential. webAI CEO and co-founder David Stout described Hale as a leader who has successfully built large-scale businesses while prioritizing data protection and user experience. He pointed specifically to Hale's leadership at ŌURA, where the company has rapidly expanded the adoption of its wearable health platform while emphasizing privacy and user ownership of personal health data. Under Hale's leadership, ŌURA has become one of the fastest-growing digital health and wearable technology companies globally, combining biometric sensing with subscription-based health insights. The company has grown significantly in both membership and revenue while navigating increasingly sensitive issues around personal health data and AI-powered personalization. Hale said the next major phase of AI development will center on "sovereign AI," a model where intelligence operates closer to the people, devices and systems using it rather than through generalized cloud-based infrastructure. He argued that truly personalized AI systems require architectures built around ownership, privacy and edge deployment from the outset. That philosophy aligns with webAI's broader positioning. The company develops private AI infrastructure and custom models designed for organizations operating in sensitive or highly regulated environments. Its platform focuses on enabling enterprises to run AI workloads with full data sovereignty, predictable operating costs and real-time performance without exposing sensitive information to third-party systems. The appointment also highlights a broader shift occurring across the AI sector as enterprises and governments become increasingly concerned about data governance, regulatory compliance and national control over AI infrastructure. Interest has grown rapidly in edge AI, private AI deployments and sovereign AI systems capable of operating independently from large centralized model providers. webAI Chairman David Shuman, who also serves as chairman of ŌURA, said the company's board is intended to function as a "judgment accelerator" supporting management during rapid growth. He noted Hale's experience scaling organizations, building software products and managing complex operational growth. Before joining ŌURA in 2022, Hale served as president of Momentive and helped oversee the company's public listing. Earlier in his career, he held senior leadership positions at HomeAway, Linden Lab, Adobe and Macromedia, giving him extensive experience across consumer software, digital platforms and subscription technology businesses. The move comes amid intensifying competition across enterprise AI infrastructure markets. While many AI companies continue emphasizing larger foundation models and centralized cloud platforms, a growing segment of the industry is focusing on secure, domain-specific and locally deployed AI systems tailored to enterprise and government requirements. webAI appears to be positioning itself directly within that trend, particularly for organizations prioritizing privacy, operational control and secure deployment environments.

webAI, an AI platform company, has appointed Tom Hale, CEO of ŌURA, to its board of directors. Hale brings over 30 years of technology and consumer products experience to the Austin-based company. At ŌURA, Hale has overseen extraordinary growth in membership, revenue and profitability since joining in 2022, building the company into one of the fastest-scaling health platforms globally. He previously served as President of Momentive, leading its public listing, and held senior roles at HomeAway, Linden Lab, Adobe and Macromedia. webAI develops AI systems focused on data sovereignty and privacy, enabling organisations to build private, custom models. The appointment comes as webAI pursues what Hale calls "Sovereign AI", bringing intelligence closer to users whilst maintaining privacy and ownership.