Agnes AI model releases

Singapore-based frontier AI startup founded in July 2025 by Bruce Yang (UC Berkeley math/CS, HEC Paris, NUS PhD candidate; earlier Microsoft and LinkedIn) with co-founder Alex Ang, building in-house full-/omni-modal foundation models across text, image, video, and reasoning. Ships the Agnes family — a consumer platform that reached several million registered users within a year — and publishes open-weights preview checkpoints alongside a proprietary production API positioned on very low per-token pricing. This page collects the lab's model releases, lifecycle events, source links, and model metadata in one crawlable record.

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Sep 14, 2026

Agnes 3.0 Flash

Agnes AI

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Agnes 3.0 Flash

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Agnes AIOpen weights

A fast multimodal model from Singapore's Agnes AI, surfaced mid-September 2026 (model card and provider coverage around Sep 14). This row reflects the disclosed open-weights PREVIEW checkpoint (Agnes-AI/Agnes-3.0-Flash on Hugging Face, Apache 2.0): a 33B-parameter model with a 262,144-token context, text/image/video input and text output, using a hybrid-attention architecture that mixes recurrent and standard attention to hold memory down at long context — of 72 decoder layers, 54 run a gated delta rule (a recurrent mechanism whose per-layer state does not grow with sequence length) while 18 use standard global grouped-query attention (24 query / 4 KV heads) and are the only layers that accumulate a KV cache. At bf16 it needs roughly 66 GB of disk and a single H100/H200-class GPU, and ships custom modeling code (trust_remote_code=True). Note the production "Agnes 3.0 Flash" served through Agnes AI's API is a different checkpoint with a 1M-token context window; the specs here are the open-weights preview. Vendor-reported figures, unverified independently at launch.

Hybrid33B262K ctxSep 14, 2026