Open AI Models

Meta's new 816B parameter mixture-of-experts model supports text, image, audio, and video inputs with a 1M token context window.

Beam is a 501B parameter Mixture-of-Experts model designed for coding and agentic tasks with a 1M token context window.

LFM2.5-24B-A2B is an open-weight Mixture-of-Experts model that uses only 2B active parameters to provide fast, private reasoning on local hardware.

The new FLUX.3 Image Klein model supports text-to-image, multi-reference image-to-image, and bounding-box layout control.

Swiss AI's Apertus 1.5 extends its 8B and 70B open-weights models with native image/audio understanding, a 262k-token context window, optional chain-of-thought reasoning, and improved tool use, trained on 4T additional tokens for the 8B model and 2T for the 70B.

TorchNeuron replaces the XLA-based torch-neuronx with a native PyTorch backend for AWS Trainium, enabling eager execution, torch.compile, and standard Hugging Face libraries without Optimum Neuron wrappers.

NVIDIA and AI4Bharat have released a 2.8 trillion token dataset and an open GPU-accelerated pipeline for generating synthetic training data in 22 Indian languages.

Granite Switch 4.1 integrates chat, decision-making, and speech-to-text capabilities into a single endpoint using efficient adapters.

HiRO-ACEv2 generates 3 km resolution global climate data at approximately 1/300th the cost of traditional high-resolution atmospheric models.

The ML-intern agent can plan, train, evaluate, and publish machine learning models on the Hugging Face Hub based on natural language descriptions.