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Mistral Large 4: document streaming and image options in the library and C API
Mistral Large 4: README (architecture, speed, agreement), reference tools
Mistral Large 4: streaming by default when too big for RAM, GPU experts in prefill, Pixtral vision
Mistral Large 4: MLA + DSA indexer + MoE text model, split GGUF, Mistral-native and FP8 checkpoints
exact attention on the matrix units with f32 operands; Step1X half-attention cost was noise
quantized Lightning runs lose far less (merge LoRA in f32, exact modulation channels)
v1.1 template, padding-token masking and reference offsets; README
Step1X-Edit (v1.2, v1.1): connector + FLUX MMDiT, Qwen2.5-VL prompt encoding, CLI, C API
instruction-based image editing, text to image and image understanding
README numbers, calcuis GGUF transformers, mapped text encoder; VAE mid-attention in query chunks
instruction editing, in-context generation and text to image
Qwen-Image-Edit (2511 / 2509 / Edit) and Qwen-Image text to image; Qwen2.5-VL
FLUX CLI: --size is the output size, and the reference image is resized to it
README section and model table rows; CLI shares --init-image with SD editing
128-wide-head attention on the matrix units; examples/flux_edit.rs
public DoubleBlock / SingleBlock (load + forward) for reuse by other FLUX-style DiTs
exact modulation vectors with quantized weights, F16 weights as stored, T5 GGUF encoders
FLUX.1 Kontext: instruction-based image editing, FLUX.1 text to image
Image editing: README section, sd_edit example, PyTorch .bin diffusers weights (MagicBrush)
Stable Diffusion image editing: img2img, inpainting, InstructPix2Pix
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