@mylifcc: This is not an ordinary large model, but a Multi-Agent Orchestration System—a small model itself that intelligently and dynamically coordinates multiple cutting-edge models such as GPT, Claude, and Gemini, autonomously assigning roles, decomposing tasks, and completing comp...
Summary
Sakana AI has released a Multi-Agent Orchestration System that uses a small model to intelligently coordinate cutting-edge large models like GPT, Claude, and Gemini to autonomously assign tasks and handle complex workloads.
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@berryxia: Small model, big wisdom? It's now real! A 7B small model now acts as the boss of top large models like GPT-5, Claude Sonnet 4, Gemini 2.5 Pro. A new paper shows an RL-trained 7B model learned to write natural language subtasks, assign them to different models, precisely...
A new paper proposes training a 7B small model via reinforcement learning as a task scheduler, automatically decomposing subtasks and assigning them to top models like GPT-5 and Claude. It surpasses individual frontier models on several hard benchmarks, demonstrating that end-to-end reward learning can effectively replace manual prompt engineering and multi-agent pipeline design.
@AYi_AInotes: Everyone is raving about Japan's Fugu beating GPT on benchmarks, but I bet 99% of people haven't understood what really makes it mind-blowing. First off, this isn't some giant monolithic model at all—it has only 0.6B parameters and essentially works as an AI project manager. It handles simple tasks on its own, automatically splits complex ones, and selects the most suitable models from a global pool of top-tier models...
Sakana AI releases Fugu, a multi-agent orchestration system with only 0.6B parameters. By intelligently splitting tasks and coordinating multiple models, it achieves state-of-the-art performance while bypassing traditional parameter scaling. This marks the transition of multi-agent orchestration from a lab curiosity to a practical productivity tool.
@vintcessun: It turns out that having multiple AI agents work together as a team is better than a single general-purpose agent in this way: each role is bound to its best model, memory and skills accumulate across conversations. Instead of taking turns, a task is handed off with a brief handover note. Runs locally, all file states are in ~/.crew44, free MIT license.
Crew44 is a local-first orchestrator that turns coding agents like Claude Code and Codex into a coordinated team of specialists, each bound to its best model, with persistent memory and skill accumulation across sessions. It runs entirely on your machine with no cloud dependence and is free under MIT license.
@EXM7777: this new AI research just dropped and it's kind of insane if you use AI agents... a tiny model that can't answer a sing…
A new AI research paper describes a tiny model that acts as a manager to route tasks to larger models, outperforming frontier models like ChatGPT, Gemini, and Claude on a hard coding benchmark by orchestrating a team of models instead of relying on a single one.
@geekbb: An open-source AI agent meta-orchestration framework that provides a unified orchestration layer for multiple agents including Claude Code, Codex, Cursor, OpenCode, Hermes, and Pi. Users can seamlessly switch sessions across devices (terminal, browser, mobile, desktop app) to enable multi-agent...
Omnigent is an open-source meta-orchestration framework that provides a unified orchestration layer over multiple AI agents like Claude Code, Codex, and Cursor. It enables seamless cross-device session switching, multi-agent collaboration, policy enforcement, and cloud sandbox execution.