Qwen-AgentWorld-35B-A3B: a 3B-active MoE trained to simulate MCP, terminal, SWE, Android, web and OS environments

Reddit r/LocalLLaMA Models
moe world-model agent-simulation tool-use environment-simulator open-source

Summary

Qwen released Qwen-AgentWorld-35B-A3B, a 35B-parameter MoE model with 3B active parameters, designed as a language world model to simulate environment responses for agent interactions across seven domains including MCP, terminal, SWE, Android, web, and OS.

Qwen just released Qwen-AgentWorld-35B-A3B — a 35B-parameter MoE with only ~3B active parameters per token. The interesting part: this is not positioned as a standard chat/instruction model or a full autonomous agent. It is a language world model trained to predict what an environment would return after an agent takes an action. It covers seven agent interaction domains: MCP / tool calling Search Terminal Software engineering Android Web Operating-system GUI interactions The intended use seems to be simulating the environment side of an agent loop: given the action history and a new tool/GUI action, predict the next observation/state. That could be useful for agent training, offline evaluation, synthetic trajectories, testing tool-use workflows, or building sandbox-like environments without constantly running the real tools. huggingface link
Original Article

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