Reflection releases Beam, a 501B-parameter open MoE model under Apache 2.0
Reflection, a new US lab, released Beam on Hugging Face: a 501B-parameter mixture-of-experts model with 23B active parameters per token, a 1M-token context window, and an Apache 2.0 license. It targets coding and agentic use cases, ships with a Rust-based harness, and has day-0 support in transformers, SGLang, and vLLM.
Sources and evidence
Summary last validated Oct 17, 2026
Reader actions
Report an issue
Use this for an incorrect summary, wrong source, duplicate story, or wrong category. Submissions are private and do not change the story automatically.
Related coverage
- models
Amazon Bedrock adds structured outputs for Anthropic Claude models
Amazon Bedrock now supports structured outputs for all Anthropic Claude models on both the bedrock-runtime and bedrock-mantle endpoints. The feature returns schema-compliant JSON matching a defined structure using JSON Schema output format and strict tool use, eliminating the need for custom parsing, retry logic, or post-processing.
- models
Cloudflare introduces Clairic System One extraction models
Cloudflare announced Clairic, a new model it describes as a System One extraction model. According to Cloudflare, Clairic can extract, compute, estimate, and forecast data from unstructured inputs. The company detailed the model in a blog post introducing the new class of extraction models.
- models
TwelveLabs Pegasus 1.5 video model launches in Amazon Bedrock
TwelveLabs' Pegasus 1.5 is now available in Amazon Bedrock. The video language model converts long-form video into structured, timestamped JSON metadata by matching user-defined moments. New features include video segmentation, multimodal prompting with reference images, and on-the-fly processing of up to two hours of video.
- models
OpenAI improves ChatGPT coding for low-resource programming languages
OpenAI published work on improving ChatGPT's performance across low-resource programming languages, introducing new evaluations covering software engineering, SQLite, and COBOL migration. The company detailed the effort in a blog post describing how it is advancing coding support beyond mainstream languages.
- infrastructure
Hugging Face and AWS release TorchNeuron for running HF models on Trainium
Hugging Face published a blog post introducing TorchNeuron, a tool for running Hugging Face models on AWS Trainium chips. The post says the integration makes deploying HF models on Trainium easier than before, though it provides no benchmark results, performance figures, or release details.