When can I download the Beam weights?

Reflection AI says it will release the Beam weights under the Apache 2.0 license later in October 2026, together with a technical report, a model card and tools for running, evaluating and fine-tuning the model. Until then, Beam is available only through an early-access waitlist on Reflection's platform.

How does Beam compare to GLM 5.2 and Qwen 3.8-Max?

Reflection AI claims Beam is competitive with larger open models like GLM 5.2 and approaches Qwen 3.8-Max on coding and agentic tasks. SiliconANGLE reports that Beam does some tasks better than GLM-5.2 while using between one third and one fourth of the hardware. These are the maker's own benchmark results, not independent tests.

How was Beam trained?

Reflection AI pretrained Beam on 23.8 trillion tokens in under four weeks on a cluster of 6,144 NVIDIA GB300 NVL72 GPUs. For the reinforcement-learning stage, Reflection used 10.5K GB300 GPUs for four weeks and generated more than 100 million rollouts, with about 1.3 billion sandboxes used for training and grading.

Is Beam good at coding benchmarks?

Reflection AI reports that Beam scores 80.9 on SWE-bench Verified, 80.1 on Terminal Bench v2.1, 78.0 on SWE-bench Multilingual and 77.2 on SWE Bench Pro v2-Hard. Reflection also lists 97.8 on AIME 2026 and 90.5 on GPQA Diamond for reasoning.

Reflection AI · 2026-10-05 · major

Beam — Reflection's 501B open-weight MoE for coding and agents

Reflection AI announced Beam, a 501B-parameter Mixture-of-Experts model with 23B active parameters for coding, reasoning and agent work. Weights arrive later this month under Apache 2.0; early access is open by waitlist.

Reflection AI announcement banner for the Beam open-weight model

Reflection AI's first open-weight model: a 501B MoE built for coding, reasoning and agent workloads.

Key specs

SWE-bench	80.9
Terminal bench v2.1	80.1

Quick facts

Maker	Reflection AI
Parameters	501B total, 23B active (sparse MoE)
Training data	23.8T tokens
License	Apache 2.0 (weights later this month)
Availability	Early-access waitlist

What is it?

Beam is Reflection AI's first open-weight language model, announced on 5 October 2026. It is a text model aimed at coding, reasoning and agentic tasks, and Reflection plans to publish its weights under Apache 2.0 later this month.

How does it work?

Under the hood, the model is a sparse Mixture-of-Experts with 501B total parameters, of which only 23B are active for each token, which keeps inference cheaper than a dense model of the same size. Reflection trained it on 23.8T tokens, extended its context in midtraining, and ran a four-week reinforcement-learning stage with more than 100 million rollouts.

Why does it matter?

A large Apache-2.0 model from a US lab gives companies and governments an open alternative to the leading Chinese open-weight models. If Reflection's efficiency claim holds, teams could run GLM-5.2-class coding agents on a fraction of the hardware.

Who is it for?

teams that self-host open models for coding agents

Frequently asked questions

When can I download the Beam weights?: Reflection AI says it will release the Beam weights under the Apache 2.0 license later in October 2026, together with a technical report, a model card and tools for running, evaluating and fine-tuning the model. Until then, Beam is available only through an early-access waitlist on Reflection's platform.
How does Beam compare to GLM 5.2 and Qwen 3.8-Max?: Reflection AI claims Beam is competitive with larger open models like GLM 5.2 and approaches Qwen 3.8-Max on coding and agentic tasks. SiliconANGLE reports that Beam does some tasks better than GLM-5.2 while using between one third and one fourth of the hardware. These are the maker's own benchmark results, not independent tests.
How was Beam trained?: Reflection AI pretrained Beam on 23.8 trillion tokens in under four weeks on a cluster of 6,144 NVIDIA GB300 NVL72 GPUs. For the reinforcement-learning stage, Reflection used 10.5K GB300 GPUs for four weeks and generated more than 100 million rollouts, with about 1.3 billion sandboxes used for training and grading.
Is Beam good at coding benchmarks?: Reflection AI reports that Beam scores 80.9 on SWE-bench Verified, 80.1 on Terminal Bench v2.1, 78.0 on SWE-bench Multilingual and 77.2 on SWE Bench Pro v2-Hard. Reflection also lists 97.8 on AIME 2026 and 90.5 on GPQA Diamond for reasoning.

Try it

https://platform.reflection.ai