Microsoft's Mage-Flow image generation model, with only 4 billion parameters, outperforms larger models including FLUX.2-dev (32B) and Qwen-Image (20B) on GenEval benchmarks, scoring 0.88 against thei…
Microsoft released Mage-Flow, a 4-billion-parameter image generation model that aims to match the quality of larger models while being smaller. The model uses a co-design approach with Mage-VAE, a lat…
Mage-Flow, a compact 4B-parameter generative stack from an unnamed research team, achieves competitive text-to-image generation and editing performance while reducing tokenization cost by more than an…
AMD GPUs running SGLang Diffusion on ROCm achieve 1.5x to 6.3x speedups over Hugging Face Diffusers for image generation and editing tasks, as demonstrated on models including FLUX.1-dev, Qwen-Image, …
Nvidia AI Labs researcher Ziv Ilan presented at GTC 2026 that video diffusion models can achieve real-time performance without 50 denoising steps by using a stack of quantization, caching, and distill…