# Reflection releases Beam, a 501B parameter open MoE model

> **Key takeaway:** Beam is a 501B parameter Mixture-of-Experts model designed for coding and agentic tasks with a 1M token context window.

**Published:** 2026-10-16T00:00:00+00:00 
**Source:** Hugging Face Blog & Announcements 
**Category:** ai-open-models 
**Canonical URL:** https://fosswire.org/news/reflection-releases-beam-a-501b-parameter-open-moe-model.html 

## Summary
The new US-based lab Reflection has released Beam, a large-scale Mixture-of-Experts (MoE) model under the Apache 2.0 license. While the model contains 501B total parameters, it only uses 23B active parameters per token, allowing for high-capacity reasoning at higher speeds. It is specifically optimized for coding, tool calling, and long-context agentic workflows.

## Technical architecture of Beam
- **Mixture-of-Experts (MoE) structure**: 52 layers total, with 49 layers utilizing 256 experts; 8 experts are routed per token.
- **Context Window**: Supports up to 1M tokens using a hybrid attention mechanism (43 sliding-window layers and 9 global layers).
- **Memory and Speed**: Requires memory for 501B parameters but operates at the computational speed of a 23B parameter model.
- **Precision Support**: Available in BF16, FP8, and NVFP4 formats.
- **Optimization**: Includes a custom Rust-based inference harness and day-0 support for transformers, vLLM, and SGLang.

## Why it matters
The Apache 2.0 release of a frontier-scale MoE model provides developers with a high-performance alternative for self-hosted agentic and coding applications.