Open Source14d ago
Ornith-1.5-122B Released Under MIT: A Single-Node 122B MoE Reasoning Model Scoring 76.9 on SWE-bench Pro
The Ornith AI team officially released Ornith-1.5-122B under the permissive MIT license, a 122-billion parameter mixture-of-experts (MoE) reasoning model optimized to execute on a single GPU node (such as a single DGX). The model is immediately available across vLLM (0.19.1+), SGLang (0.5.9+), Hugging Face, and Ollama (ornith-1.5:122b) with native FP8, GGUF, and MLX quantization. Across independent agentic evaluations in the OpenHands harness, Ornith-1.5-122B registered 84.5 on SWE-bench Verified, 76.9 on SWE-bench Pro (surpassing Qwen3.8-Flash-Next's 43.9 by 33 points), 81.2 on TerminalBench 2.1, and 74.6 on MCP-Atlas.
Open Source14d ago
Ant Group Open-Sources Ming-3.0-tts: 93.2% Pronunciation Accuracy Leading Global Open Speech Models
In the latest independent Text-to-Speech (TTS) evaluations published by Artificial Analysis, Ant Group's open-source Ming-3.0-tts achieved a 93.2% pronunciation accuracy score, ranking #1 among all 31 evaluated models (outperforming commercial leader ElevenLabs v4 at 91.7%). Offering both a dense 0.5B parameter variant and a 7.9B mixture-of-experts (MoE) model, it delivers voice cloning and preset voices with a Controlled Voice Elo score of 1,069 (#1 among open-weight models), fully released under the permissive MIT license.
Models22d ago
Kandinsky 6.0 Video Released: Open-Source Foundation Models for Synchronized 1080P Video and 44kHz Audio Generation
Generating cinematic video accompanied by synchronized, high-fidelity audio represents a premier frontier in multimodal AI. Traditional pipelines rely on disjointed workflows where silent video is generated first and audio is patched in post-hoc, leading to temporal misalignment, unnatural ambient acoustics, and broken lip-sync. The Kandinsky research team releases Kandinsky 6.0 Video (arXiv:2610.05608, code: github.com/kandinskylab/kandinsky-6, Hugging Face Diffusers integration). Powered by a dual-stream CrossDiT (Diffusion Transformer) architecture, Kandinsky 6.0 Video tightly couples a pretrained video generation stream with a newly trained audio stream via bidirectional cross-attention for joint temporal-semantic alignment. Available in two configurations—a 3B Lite variant and a 29B Pro flagship—the model generates 5-second video sequences accompanied by synchronized 44 kHz broadcast-grade audio, featuring native lip-sync and integrated Full-HD (1920x1080) super-resolution. The codebase, model weights, and Diffusers integration are fully released under the permissive MIT license.
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