Cerebras-GPT

Stable LM: Stability AI Language Models. The release of Stable LM builds on our experience in open-sourcing earlier language models with EleutherAI, a nonprofit research hub. These language models include GPT-J, GPT-NeoX, and the Pythia suite, which were trained on The Pile open-source dataset. Many recent open-source language models continue to build on these efforts, including Cerebras-GPT and Dolly-2. Stable LM is trained on a new experimental dataset built on The Pile, but three times larger with 1.5 trillion tokens of content. We will release details on the dataset in due course. The richness of this dataset gives Stable LM surprisingly high performance in conversational and coding tasks, despite its small size of 3 to 7 billion parameters (by comparison, GPT-3 has 175 billion parameters). Stable LM 3B is a compact language model designed to operate on portable digital devices like handhelds and laptops, and we’re excited about its capabilities and portability.

MiMo-V2.6-Flash is an open-source, natively omnimodal AI model from Xiaomi MiMo designed to balance intelligence, efficiency, and cost. The model supports coding, general agent workflows, visual reasoning, computer use, automation, and multimodal creative tasks. Its capabilities extend beyond software engineering into frontend design, presentation creation, 3D modeling, interactive world generation, video production, and embodied simulation. Xiaomi trained MiMo-V2.6-Flash with large-scale reinforcement learning across coding, general agent, visual, and cybersecurity tasks, completing roughly 750,000 training trajectories. The model is positioned as the more cost-efficient member of the MiMo-V2.6 family while retaining strong performance across software engineering, tool use, automation, and visual coding benchmarks. MiMo-V2.6-Flash is available through MiMo Desktop, AI Studio, MiMo Code, the Xiaomi MiMo API Platform, OpenRouter, and the open-source MiMo-V2.6 release.