{
  "video_id": "reddit_1ue56em",
  "channel_slug": "LocalLLaMA",
  "channel_handle": "r/LocalLLaMA",
  "title": "Qwen-AgentWorld-397B-A17B",
  "url": "https://www.reddit.com/r/LocalLLaMA/comments/1ue56em/qwenagentworld397ba17b/",
  "external_url": null,
  "upload_date": "20260624",
  "published_at": "2026-06-24T06:00:39+00:00",
  "transcript": "It looks like a new model, mentioned on [https://huggingface.co/Qwen/Qwen-AgentWorld-35B-A3B](https://huggingface.co/Qwen/Qwen-AgentWorld-35B-A3B)\n\nand on https://qwen.ai/blog?id=qwen-agentworld\n\n\n\n--- Top Comments ---\n\n\n[25 upvotes] I had a short look into the blog. \n\nIt seems to be a model created to simulate environments for training agentic capabilities. It simulates the \"world\" so you don't have to setup a \"real gym\" for simple tasks. \n\nMight be very suitable for bootstrapping RL\n\n[12 upvotes] https://preview.redd.it/9brjsu7vh69h1.png?width=6928&format=png&auto=webp&s=c82bcd6abd22496dbdee31f14bd10289c84e5852\n\nSWE? Really?\n\n[8 upvotes] Seems very interesting. It looks like they implemented what LeCun has been advocating on having action output entangled with the loss while training the model (thus making this a \"world model\", I guess?). Depends on their dataset, but I wouldn't be surprised this wipes the floor with the baseline model. Also 35b is very close to 397b. I wonder how well it does with real agentic tasks. But in any case, very interesting stuff!\n\n[7 upvotes] No 397-A17B weight",
  "transcript_chars": 1108,
  "ingested_at": "2026-06-24T13:30:05.123985+00:00",
  "source": "reddit",
  "yt_meta": {
    "score": 66,
    "upvote_ratio": 0.91,
    "num_comments": 15,
    "author": "Shoddy_Bed3240",
    "is_self": true
  }
}