Tagged articles

Mixture-of-LoRA

5 articles · Page 1 of 1

Jul 26, 2026 · Artificial Intelligence

Beyond Scaling: How Macaron‑V1 Opens a New Path for Continuous Learning in Open‑Source AI

Macaron‑V1, built on the GLM‑5.2 foundation, demonstrates that post‑training growth via LoRA‑based Mixture‑of‑LoRA, recursive self‑improvement and multi‑agent collaboration can outperform larger static models on benchmarks like UI4A, while its supporting infrastructure (MinT, MindForge, LongStraw) makes million‑parameter reinforcement learning feasible.

AI infrastructureLoRAMacaron-V1

0 likes · 19 min read

Beyond Scaling: How Macaron‑V1 Opens a New Path for Continuous Learning in Open‑Source AI

Machine Learning Algorithms & Natural Language Processing

Jul 24, 2026 · Artificial Intelligence

China’s 00‑Gen AI Team Unveils 748B LoRA Model Matching Opus 4.8 Performance

Mind Lab’s newly released Macaron‑V1, a 748‑billion‑parameter model built from a GLM‑5.2 base plus four specialized LoRA adapters, achieves benchmark results comparable to Opus 4.8, GPT‑5.5 and Gemini 3.1 Pro, while demonstrating the industry’s shift toward continuous‑learning AI through Mixture‑of‑LoRA architecture and open‑weight deployment.

AI modelLoRAMixture-of-LoRA

0 likes · 16 min read

China’s 00‑Gen AI Team Unveils 748B LoRA Model Matching Opus 4.8 Performance

Machine Heart

Jul 24, 2026 · Artificial Intelligence

Beyond Bigger: Macaron‑V1 Introduces Continuous Learning and Collective Intelligence

Macaron‑V1, an open‑source model built on the GLM‑5.2 base, demonstrates that scaling alone is insufficient by integrating LoRA‑based continuous learning and multi‑agent collaboration, achieving superior benchmark scores, efficient parameter updates, and a novel infrastructure that supports millions of adapters and long‑context reinforcement learning.

Large Language ModelsLoRAMacaron-V1

0 likes · 18 min read

Beyond Bigger: Macaron‑V1 Introduces Continuous Learning and Collective Intelligence

SuanNi

Jun 8, 2026 · Artificial Intelligence

Agent Harness Model Achieves Frontier Performance at <1% Compute Cost – Introducing Macaron‑V1‑Preview

A 30‑person lab trained a 749B‑parameter Agent model called Macaron‑V1‑Preview using fewer than 300 GPUs, achieving less than 1% of the compute cost of comparable models while matching state‑of‑the‑art performance on real‑world Agent benchmarks such as LivingBench, VitaBench, A2UI and PinchBench.

AIAgentEfficient Training

0 likes · 15 min read

Agent Harness Model Achieves Frontier Performance at <1% Compute Cost – Introducing Macaron‑V1‑Preview

Machine Learning Algorithms & Natural Language Processing

Jun 8, 2026 · Artificial Intelligence

MindLab Unveils 749B Agent-Optimized Macaron‑V1‑Preview Model

MindLab released the 749B‑parameter Macaron‑V1‑Preview, a model engineered for deep Agent‑Harness post‑training that was trained on fewer than 300 GPUs at less than 1% of the compute cost of peer models and achieves SOTA results on multiple Agent‑centric benchmarks such as LivingBench, VitaBench and PinchBench.

Agent HarnessEfficient TrainingLoRA