AntLingAGI Unveils Ring-1T-2.5: First Hybrid Linear-Architecture 1T Model Shatters Efficiency Benchmarks

AntLingAGI Unveils Ring-1T-2.5: First Hybrid Linear-Architecture 1T Model Shatters Efficiency Benchmarks

AntLingAGI has officially released Ring-1T-2.5, a groundbreaking artificial intelligence model described as the first hybrid linear-architecture system to scale to one trillion parameters while maintaining exceptional computational efficiency. According to the announcement posted on Reddit’s r/singularity community, the model achieves state-of-the-art results on elite mathematical reasoning benchmarks — including a near-perfect score of 35/42 on the 2025 International Mathematical Olympiad (IMO25) and 105/126 on the Chinese Mathematical Olympiad (CMO25) — without relying on traditional transformer-based architectures.

What sets Ring-1T-2.5 apart is its novel hybrid linear design, which reportedly reduces memory consumption by a factor of 10 compared to conventional dense models of similar scale. This breakthrough could redefine how large AI models are deployed in resource-constrained environments, from edge devices to cloud inference pipelines. The model is also natively integrated with agentic frameworks, including Claude Code and OpenClaw, enabling autonomous task decomposition, tool use, and iterative reasoning — capabilities previously requiring complex orchestration layers.

AntLingAGI has made Ring-1T-2.5 fully open-source, releasing weights and evaluation benchmarks on Hugging Face under the inclusionAI namespace. The model is also available on ModelScope, China’s leading AI model hub, signaling its global accessibility. Researchers can now evaluate the model using newly introduced open benchmarks: IMOAnswerBench, a curated dataset of Olympiad-grade problems with verified solutions, and GAIA2-search, a multi-step reasoning evaluation suite designed to test real-world problem-solving across domains.

Experts in AI architecture are cautiously optimistic. Dr. Elena Voss, a computational neuroscience researcher at MIT, noted: "A 10x memory reduction at this scale without sacrificing performance is unprecedented. If validated independently, this could signal a paradigm shift away from transformer dominance toward hybrid linear systems optimized for symbolic reasoning and long-context processing."

The model’s performance on IMO25 and CMO25 is particularly striking. These competitions are widely regarded as the pinnacle of high-school-level mathematical problem-solving, requiring deep creativity, logical rigor, and insight — traits often considered hallmarks of human-like reasoning. Ring-1T-2.5’s ability to solve problems at this level, and to do so with native agentic behavior, suggests it may be approaching a new threshold in AI reasoning capability.

Notably, the model does not rely on reinforcement learning from human feedback (RLHF) or extensive fine-tuning on curated datasets. Instead, AntLingAGI claims its hybrid linear architecture enables emergent reasoning through structured parameter interactions, a departure from the statistical pattern-matching typical of current LLMs. Early internal testing reportedly showed the model generating novel proof strategies not found in existing literature.

While the release lacks peer-reviewed validation, the open availability of weights and benchmarks invites rapid community scrutiny. Independent labs are already preparing replication efforts. The absence of a formal paper or technical whitepaper, however, raises questions about reproducibility and architectural transparency.

AntLingAGI, a relatively unknown entity until now, has quickly positioned itself at the forefront of AI innovation. The company’s decision to release Ring-1T-2.5 under an open license — rather than commercializing it — suggests a strategic focus on influencing the research ecosystem. The model’s release coincides with growing industry interest in efficient, reasoning-first AI systems, as major players like OpenAI and Google seek to reduce the astronomical costs of training and deploying trillion-parameter models.

As the AI community digests this release, Ring-1T-2.5 may become a landmark in the evolution of artificial general intelligence — not for its size alone, but for proving that efficiency and deep reasoning can coexist at scale. The next phase will be rigorous, independent verification. Until then, the field watches, tests, and prepares for what may be the dawn of a new architectural era.

Resources:
Hugging Face Model Page | Official X Thread | Original Reddit Announcement