Apodex is a reasoning-first Mixture-of-Experts model family built by the Apodex team for complex long-horizon research, forecasting, and verifiable reasoning tasks. An agent runtime supplies file, data, code, and tool execution; the core API accepts text only.
When a research agent runs 25, 100, or 2000 turns, what happens? Context suffocation: information piles up, noise increases, attention gets diluted. IterResearch solves this with Markovian state reconstruction; AREX achieves recursive self-improvement with an inner/outer loop. Both answer: how does an agent stay coherent across hundreds of search rounds?
OneDayAgent's decompose-remember-verify harness hits 0.821 new SOTA on AgentIF-OneDay and works unchanged across five backends; The Horizon Gap surveys 1,547 papers to find that six categories of long-horizon failure share a single structural pattern — outcome-only signals degrade as step count grows, driving the field toward denser process signals; Evo-Bench is the first benchmark for harness self-evolution — GPT-5.6 Sol peaks at +16.6 absolute gain, but Office tasks still need hand-crafted workflows