Ex-Huawei Noah's Ark Lead's Startup Ships NeoHorse: Baking Multi-Model Harness Experience Into a 4B Agent Model
量子位 · wechat · 2026-09-08
Jiyuan Lvdong, founded by former Huawei Noah's Ark Lab director and Pangu model lead Wang Yunhe, released its first Agent-Native model NeoHorse, with compute and infra from Infinigence and algorithm research from Tsinghua and PKU teams. NeoHorse-1 comes in 4B and 9B, targeting tool calling, environment feedback reading, error recovery, and path adjustment. After Agentic Post-Training, the 4B (macro average 58.94→64.87) beats its base Qwen3.5-4B across 10 benchmarks, reaching same-scale SOTA.
Core idea: train on Harness execution logs
- Training corpus combines RoutingHarness Agent execution signals—router decisions, model switches, failure-and-recovery traces, environment verification. Failure trajectories add knowledge about where errors occur and how to adjust.
- Each trajectory passes structural checks and is scored on six quality dimensions; Routing-Guided Curriculum orders samples easy-to-hard; On-Policy Distillation has the teacher coach the student at its actual steps.
Business stack and the RSI narrative
The company has four layers: open-source OpenSquilla, TokenRhythm API (a Chinese OpenRouter analog), enterprise services, and now NeoHorse—validating a flywheel from execution experience to training data to model capability. The company frames it as a single-round engineering validation toward RSI (Data-RSI + Model-RSI), though reward and signal design remain human-set and multi-generation gains are unproven. Key risk: DeepSeek, Qwen and others are vertically integrating models with Harness/Agent infrastructure, squeezing the middleware layer.
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