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New models and versions from OpenAI, Anthropic, Google, Meta, Mistral, xAI, DeepSeek, Qwen and others.

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“Open Source” — 3 articles ✕

Models· Important

Reflection releases Beam, a 501B open-weight MoE model with 1M-token context

Reflection, a new US AI lab, has launched Beam, its first model, as an open-weight mixture-of-experts system with 501B total parameters (23B active per token) and a 1M-token context window, released under Apache 2.0. The model is built for coding and agentic use cases, ships with a custom Rust-based inference harness, and has day-0 support in transformers, vLLM and SGLang. Reflection reports strong results on coding, reasoning and tool-calling benchmarks across BF16, FP8 and NVFP4 checkpoints.

Hugging Face
Models· Important· 🧪 Worth Testing

IBM combines transcription, decision-making and chat in a single Granite Switch model

IBM has released Granite Switch 4.1 in 8B and 30B sizes, a modular system that runs chat, decision-making and speech transcription from one hosted endpoint instead of separate models. The update adds a general-purpose Decision adapter, a specialized Guardian adapter for safety-related classifications, and an embedded ASR model, Granite-Speech-5.0-Turbo-CTC, which tops the OpenASR Leaderboard. Despite bundling three capabilities, the combined model uses roughly the same VRAM as the base model alone.

Hugging Face
Models· Important

Mistral releases Timestral, a time-series forecasting model family

Mistral AI has launched Timestral, its first family of time-series foundation models, available in four sizes from 5M to 209M parameters. The largest model ranks first on all three major public forecasting benchmarks (GIFT-Eval, TIME, fev-bench), beating previous state-of-the-art models that have more parameters. The models produce probabilistic, multivariate forecasts, support past and known-future covariates, and run efficiently on CPUs without needing a GPU.

Mistral AI