Search-R1 alternatives
Curated alternatives to Search-R1 — and why you'd switch.
OpenResearcher
TIGER-AI-Lab's fully open deep-research recipe: 96K long-horizon trajectories (adopted by NVIDIA Nemotron), a 30B-A3B model hitting 54.8% BrowseComp-Plus, training code and eval harness.
Why switchTwo open deep-research training recipes: OpenResearcher ships trajectories + a trained model; Search-R1 ships the RL framework to train your own from scratch.
Full comparison →hyperresearch
Deep-research harness for Claude Code: a 16-step, tier-adaptive pipeline with adversarial critics, cite-checking and 250+ sources per run, every source kept in a persistent markdown+SQLite vault.
Why switchTwo routes to a deep-research agent: hyperresearch engineers the harness around a frontier model (16 steps, adversarial critics), search-r1 trains the search behaviour into the weights with RL.
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