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The user praises the Ling 3.0 Tiny AI model for being fast and efficient on low-end PCs, comparing it favorably to models like Qwen 3.5 9b and Gemma 12.
Release of Ling-3.0-tiny, a hybrid reasoning model with 7.9B total parameters and only 1.3B active per token, free for a week.
A small model designed to summarize the reasoning traces of coding agents, helping improve interpretability and efficiency.
SupraLabs released SupraSafety-18M, a tiny 18M-parameter BERT-style content moderation model trained on NVIDIA's Nemotron-3.5 dataset. It achieves 81.2% accuracy and runs efficiently on edge devices.
The paper introduces VGB, a process-guided sampling algorithm with probabilistic backtracking, which significantly improves coding performance on tiny 0.5B models by being robust to verifier errors.
Inflect-Nano-v1 is a tiny English text-to-speech model with 4.63M total inference parameters, including its vocoder, designed for local, efficient speech synthesis experiments.
Built a repository to train a tiny language model (25M parameters) from scratch on 8GB VRAM, with support for MTP but noting limitations of mHC and BitNet.