SupraLabs has launched supra-title-FFT-preview, a chat title generation model trained on 115K samples from a filtered dataset, expanding coverage beyond its previous 12K-sample model. The model uses full fine-tuning on LiquidAI/LFM2.5-350M-Base with BF16 precision and is designed for single-purpose chat title generation, available via Hugging Face and supporting direct loading or vLLM deployment.
SupraLabs Releases supra-title-FFT-preview with 115K Samples
What are people doing with their local models and what tools do they use?
A user asks about practical applications of local models and which tools are effective for tasks like coding, particularly as alternatives to web-based interfaces like Claude.ai. They mention trying OpenWebUI but find it underpowered without significant customization.
North Mini Code: 4-bit quant, Ollama, and OpenRouter support
Cohere Labs has released a 4-bit quantized version of North Mini Code on Hugging Face, reducing its size to approximately 20GB for local execution on devices like Macs. The model is now supported in Ollama, local runtimes based on llama.cpp, and via the OpenRouter API, improving accessibility for developers.
Donate your coding sessions to an open CC-BY-4.0 dataset
A project called Trace Commons invites users to donate their coding session traces to an open dataset licensed under CC-BY-4.0. The initiative aims to provide training data for open-weight and open-source AI models, countering potential data monopolies by Anthropic and OpenAI.
NVIDIA buys HuggingFace for $13B; Z.ai launches GLM-5.3-Flash
Nvidia is acquiring HuggingFace for $13 billion, nearly double its initial January 2026 offer, as the platform doubles its customer base in 2026. Simultaneously, Z.ai has formally launched GLM-5.3-Flash, a natively multimodal open-weight model previously known as Ox Alpha.
Z.ai launches GLM-5.3-Flash, a 320B-parameter multimodal model with 1M context
Z.ai has formally launched GLM-5.3-Flash, revealing that the previously previewed "Ox Alpha" model is its public identity. The model features 320 billion total parameters with 18 billion active, a 1 million-token context window, and native multimodal capabilities.