Reflection Open-Sources Beam-1.0, a 501B-Parameter MoE with 1M Context
On October 16, Reflection AI released Beam-1.0, its first open-weight model — a MoE architecture with 501B total parameters and 23B active per token, supporting a 1M token context. It is open-sourced under Apache 2.0, targets coding, reasoning, and agent tasks, and launched alongside 40+ ecosystem partners (Nebius, Ollama, Databricks, AWS, Google Cloud, NVIDIA, and others).
Confirmed
- Model specs: 501B MoE, 23B active per token; 52 layers, 256 experts per layer with 8 routed; 1M token context
- Full collection available on Hugging Face, including the original Beam-1.0-501B-A23B plus FP8 and NVFP4 quantized versions and a DFlash2 version
- The release also includes optimized inference support, quantized weights, and a coding harness
- Hugging Face team benchmarks: SWE-bench at 81.6%, with the NVFP4 quantized version showing almost no performance drop
- Licensed under Apache 2.0, focused on token efficiency for coding and agent use cases
Why it matters
Beam is Reflection AI's first open-weight model, fully open under Apache 2.0 with quantization and deployment tooling included, and backed by 40+ cloud and tooling partners — significantly lowering the barrier to enterprise adoption. HF benchmarks show the NVFP4 quantization is nearly lossless, meaning coding and agent capabilities close to the original can be retained even on low-precision hardware, putting direct competitive pressure on the open-source coding/agent model landscape.
2026-10-16 ~ 2026-10-16 · 20 related posts
- Episode 1: Reflection Open-Sources Beam-1.0, a 501B-Parameter MoE with 1M Context(2026-10-16, 20 posts)
- Episode 2: vLLM Details Beam Architecture and Kernel-Level Long-Context Optimizations(2026-10-16, 2 posts)
Primary sources
- Reflection releases open MoE Beam-1.0: 501B total/23B active, 1M context, 3x fewer reasoning tokens — jacek2023 ·
- Reflection launches Beam 1.0: open-weight 501B/23B model with 1M context under Apache 2.0 — bhutanisanyam1 ·
- Beam benchmarks: SWE-bench 81.6%, NVFP4 quantization barely hurts, fits 4×B200 — ben_burtenshaw ·
- [source] Reflection launches Beam 1.0: open-weight 501B/23B model with 1M context under Apache 2.0 — bhutanisanyam1 · 2026-10-16
- [source] Beam benchmarks: SWE-bench 81.6%, NVFP4 quantization barely hurts, fits 4×B200 — ben_burtenshaw · 2026-10-16
- Beam 1.0 collection lands on Hugging Face with FP8, NVFP4 and DFlash2 variants — victormustar · 2026-10-16
- Reflection's First Open-Weight Model Beam Debuts: 501B-Total MoE With 23B Active, Built for Coding and Agents — baseten · 2026-10-16
- Reflection's Beam: a 501B MoE open model with 1M context, Apache 2.0, agentic focus — mervenoyann · 2026-10-16
- vLLM ships Day-0 support for Reflection-Beam-1.0, a 501B-param MoE with 1M context — vllm_project · 2026-10-16
- [source] Reflection releases open MoE Beam-1.0: 501B total/23B active, 1M context, 3x fewer reasoning tokens — jacek2023 · 2026-10-16
- Reflection AI's 501B open model Beam fine-tunes with LoRA on a single 8x B300 node — QGallouedec · 2026-10-16
- Ollama Lists Reflection's Beam: 501B/23B MoE With 1M Context and Tool Support — ollama · 2026-10-16
- Reflection open-sources 501B MoE Beam; vLLM day-0 support hits 708 tokens/s — Xianbao_QIAN · 2026-10-16
10 near-duplicate retellings: ben_burtenshaw · bhutanisanyam1 · paf1138 · tomaarsen · tomaarsen · victormustar · QGallouedec · zhyncs42 · arena · AI4Code