Beam 1.0
Description
Beam 1.0 is Reflection AI's first open-weight model: a sparse Mixture-of-Experts reasoning model with 501.3B total parameters and 23.4B active per token (52 layers: 3 dense + 49 MoE; 256 experts; gated GQA with sliding-window attention; 152K vocabulary), pretrained on 23.8T tokens and post-trained with large-scale asynchronous RL. It targets coding, long-horizon agentic work, and tool use, with a 1M-token context window, up to 128K output tokens on the Reflection API, text-only input/output, and mandatory reasoning with low/medium/high/xhigh/max effort levels. Released under Apache 2.0 in BF16, FP8, and NVFP4 with a DFlash speculative-decoding drafter; available on Hugging Face, the Reflection API (Beam-1.0-501B-A23B), OpenRouter, and other partners.
Capability Radar
Science is estimated from LLM Stats science scores or reasoning when no dedicated science benchmarks are available.
Rankings
| Domain | #Rank | Score | Source |
|---|---|---|---|
| Agentic Capability | 19 | 62.0 | LS |
Benchmark Scores (LLM Stats)
(LLM Stats (zeroeval))Agents
Code
Instruction Following
Knowledge
Long Context
Math
Reasoning
Search
AA Evaluation Indices
(Artificial Analysis)No AA evaluation data available
LLM Stats Category Scores
(LLM Stats (zeroeval))Pricing
Speed
No speed data available
Provider Price Ranking
Provider Price Ranking
4 providers
Compare pricing across different API providers for this model.