the first open-weights model from Reflection, a 501B-total, 23B-active mixture-of-experts built for agentic tool use, coding and general reasoning. it reads text only and its weights ship under Apache 2.0.
pick it if
you want a long-window text model priced with the flash tier
you want Apache 2.0 weights, with BF16, FP8 and NVFP4 builds to self-host
you run tool-calling agents on text and repeat long prompts, so cached input matters
skip it if
you need image, audio or video input; Beam reads text only
long autonomous coding is the job; its reported DeepSWE v1.1 score sits below GLM-5.3 Flash and DeepSeek V4.1 Flash
the first natively multimodal model in Zhipu AI's GLM-5 series, an open-weights 320B-total, 18B-active sibling of GLM-5.3. it costs about a ninth of GLM-5.3's per-token rate and, unlike GLM-5.3, accepts image and video input.
pick it if
you want GLM-5.3-family text at roughly a ninth of the price
you need image or video input in the GLM line
you want MIT-licensed weights you can self-host
skip it if
you need replies without thinking; Z.ai says thinking cannot be disabled
faq
which is better, Beam or GLM-5.3 Flash?
on Terminal Bench 2.1, as each maker reports it, Beam scores 80.1% and GLM-5.3 Flash 84.3. these are each maker's own numbers, not a controlled head-to-head; the spec table lists every benchmark both publish.
which is cheaper, Beam or GLM-5.3 Flash?
Beam lists lower input and output prices. on a coding-agent session (2M tokens in, 60,000 out) Beam costs $0.27 and GLM-5.3 Flash $0.33.
which one accepts images?
GLM-5.3 Flash supports vision; Beam does not.
can i switch between Beam and GLM-5.3 Flash mid-task?
yes. in an octomind session, /model octohub:beam and /model octohub:glm-5.3-flash switch models without losing the conversation, so you can draft on one and review on the other.
try either model
switch between models inside the same octomind session.