Rednote Open-Sources dots3-note: 280B Multimodal Agent Model with 512K Context

On August 29, Rednote's AI lab dots studio released dots3-note Preview, an open-source multimodal agent model built for long-horizon, evolving real-world tasks. It has 280B total / 16B active parameters (MoE), a 512K context window, text-vision-audio understanding, and ships under Apache 2.0 — the first tri-modal model in the dots3 family — with early benchmark results drawing community attention.

Confirmed

• Specs: 280B total / 16B active parameters, 512K context, Apache 2.0 license
• Multimodal: joint understanding of text, vision, and audio; first tri-modal model in the dots3 family
• Positioning: workflows requiring sustained reasoning, execution, and dynamic adaptation, addressing plan coherence in long-horizon agent tasks
• Training: per @heyshrutimishra, the core innovation is the TEMPO training method targeting task persistence
• Capability loop: stronger coding, tool calling, and end-to-end delivery close the loop from perception to action
• Official demo: autonomously building a Xiaohongshu (Rednote) VR experience
• Benchmarks: per @heyshrutimishra, ARC-AGI-2 score of 81.39 and SWE-bench Verified of 78.4%

Unconfirmed

• Exact evaluation settings and reproducibility of the benchmark scores await official technical reports or independent community testing

Why it matters

dots3-note is among the few open models combining ultra-long context with tri-modal understanding under a permissive license, offering a new foundation for agent applications needing long-term memory and multimodal interaction. Its 512K context and sparse activation design target long-horizon coherence, and its reported scores on hard benchmarks like ARC-AGI-2 and SWE-bench Verified make community replication worth watching.

2026-08-29 ~ 2026-08-31 · 9 related posts

Full story(2 episodes)→

• Episode 1: Rednote Open-Sources dots3-note: 280B Multimodal Agent Model with 512K Context(2026-08-29, 9 posts)
• Episode 2: dots3-note Demonstrated as Long-Horizon Agent in Wedding Planning Test(2026-08-30, 2 posts)

• rednote explores open-weight multimodal model with 512K context for long-horizon agents — aftahi_ai · 2026-08-29
• [source] dots3-note Preview: 280B Params, 512K Context for Long-Horizon Tasks — mhdfaran · 2026-08-29
• dots3-note Preview Launched: 280B Total/16B Active, 512K Context, Multimodal — SarahAnnabels · 2026-08-30
• dots3-note Preview: first dots3 model to jointly understand text, vision and speech — SarahAnnabels · 2026-08-30
• RedNote releases dots3-note: 280B open-weight model for long-horizon tasks — heyshrutimishra · 2026-08-31
• Rednote open-sources dots3-note: 16B active params hits 78.4% on SWE-bench — heyshrutimishra · 2026-08-31
• Dots3-Note Preview: 16B active parameters model tops multiple benchmarks — heyshrutimishra · 2026-08-31

2 near-duplicate retellings: SarahAnnabels · heyshrutimishra