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
MiniMax M3 is MiniMax's open-weight model (about 428B total, 23B active parameters) for coding and agent work, with image and video input. in this catalog it costs twice MiniMax M3.1 Flash, the newer October 2026 release.
pick it if
you need image and video input at $0.30 / $1.20 per million
you want open weights you can also self-host
you reuse long prompts: cache hits bill at a fifth of input
skip it if
MiniMax M3.1 Flash, at half the price, covers your workload
you need JSON-schema constrained output
faq
which is better, Beam or MiniMax M3?
on Terminal Bench 2.1, as each maker reports it, Beam scores 80.1% and MiniMax M3 66.0%. 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 MiniMax M3?
Beam lists lower input and output prices. on a coding-agent session (2M tokens in, 60,000 out) Beam costs $0.27 and MiniMax M3 $0.67.
which one accepts images?
MiniMax M3 supports vision; Beam does not.
can i switch between Beam and MiniMax M3 mid-task?
yes. in an octomind session, /model octohub:beam and /model octohub:minimax-m3 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.