Qwen-AgentWorld-35B-A3B: a 3B-active MoE trained to simulate MCP, terminal, SWE, Android, web and OS environments
Mirrored from r/LocalLLaMA for archival readability. Support the source by reading on the original site.
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.
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