Tools, frameworks, and models for local AI
5 resources found for "Open Weight"
A 5.6B open-weights image model for text-to-image, single-reference editing and multi-reference composition in one model, with placement boxes in the prompt. Qwen3-VL-4B text encoder. In BF16 (11.1GB), FP8 and NVFP4 (5.3GB). FLUX Kommunity license (non-commercial + qualified-user exception).
Modello MoE open-weight di inclusionAI: 560B parametri totali, 25B attivi per token, architettura ibrida (attenzione lineare KDA + Gated MLA), finestra di contesto fino a 1M di token, licenza MIT. Reasoning ibrido con modalità di pensiero on/off. A 4 bit entra in 512GB di memoria unificata.
Kandinsky Lab's foundation models for synchronized video and audio generation: from a prompt they generate video clips with aligned audio, released as open weights. Top paper of the day on Hugging Face (2026-10-06), with checkpoints and Spaces already available.
Il primo 'modello unificato' di Mistral: dense da 128B che unisce instruction-following, reasoning e coding in un'unica serie di pesi, sostituendo Medium 3.1, Magistral e Devstral 2. Multimodale (testo+immagini), contesto 256K, ragionamento configurabile. Open weights con licenza Modified MIT: uso libero fino a una soglia di fatturato per le grandi aziende.
NVIDIA's vision encoder-decoder family for local document understanding: markdown, LaTeX formulas, bounding boxes and a semantic class per element, in reading order. ViT-H (C-RADIO) + 10-block mBART decoder, all under 1 billion parameters. Locally via vLLM (v0.20–v0.26 for 2.0) or Transformers, on NVIDIA GPUs (Turing through Blackwell).
