The repository stepfun-ai/Step-5-Preview-BF16 has been published to Hugging Face. The submission title indicates that the model appears promising.
media
r/LocalLLaMA
·
3d ago
·
open_models
Stepfun releases Step-5-Preview-BF16 model on Hugging Face
from English
Related articles
media
TLDR AI
·
2h ago
·
10 views
Xiaomi open-sources MiMo-V2.6 Pro and Flash models
Xiaomi has open-sourced the MiMo-V2.6 Pro and Flash omnimodal models, which are designed to coordinate agents for constructing and visually testing interactive 3D scenes. These models can generate Blender assets, control robotic arms from camera feeds, produce frontends and presentations, assemble videos, and compose music as scores and MIDI.
media
r/LocalLLaMA
·
15h ago
·
14 views
AntLing open sources Ming-Image-0.1-Design family of 6B models
AntLing has released the Ming-Image-0.1-Design family, which includes two 6B parameter models: Ming-Image-0.1-Design and Ming-Image-0.1-Design-Layer.
media
Latent Space
·
23h ago
·
11 views
Xiaomi releases MiMo-V2.6-Pro, a top open-weights omnimodal model trained for $3M
Xiaomi has released the MiMo-V2.6 series, introducing natively omnimodal models including MiMo-V2.6-Pro and MiMo-V2.6-Flash. The company also launched MiMo-V2.6-Pro-UltraSpeed, which delivers up to 20x faster output speed at the same quality.
media
MarkTechPost
·
1d ago
·
9 views
AWS Strands Agents releases open-source Strands Harness with lower token cost
The AWS Strands Agents team has released Strands Harness, an open-source, general-purpose agent harness available under the Apache 2.0 license for Python and TypeScript. The tool is designed to bridge the gap between prototyping agents in environments like Claude Code or Codex and deploying them with custom loops.
lab
Microsoft Research Blog
·
2d ago
·
30 views
Microsoft releases RetroChimera for retrosynthesis prediction
Microsoft Research has published and open-sourced RetroChimera, a new framework for retrosynthesis prediction that combines two complementary models to propose high-quality synthesis routes. The system integrates R-SMILES 2, a Transformer-based de-novo model, with NeuralLoc, a graph neural network (GNN) based model, using a learned ensembling strategy to rank predictions.