{
  "video_id": "reddit_1to73op",
  "channel_slug": "LocalLLaMA",
  "channel_handle": "r/LocalLLaMA",
  "title": "Okay 27B made me a believer",
  "url": "https://www.reddit.com/r/LocalLLaMA/comments/1to73op/okay_27b_made_me_a_believer/",
  "external_url": null,
  "upload_date": "20260526",
  "published_at": "2026-05-26T13:32:53+00:00",
  "transcript": "I previously hated on this model, but I have just been impressed by it, and I understand the hype now.\n\nI have been working on a HTML5 game console and I decided to see if Qwen3.6 27B can handle making some quick games in it to showcase functionality (save games, console API handling for stat tracking and heartbeat management, meta data for the game, etc)\n\nI gave it 3 files, explaining how the API works, the gamepad controls, and a typescript shader for it to apply. Then I just game it a very simple prompt \"make a breakout game for this console, in the working directory are reference files on how to make it\".\n\nFirst result was immediately playable, controls made sense, graphics style was was unique and appropriate, sound worked, console API all worked, and it felt good and was actually fun. It added flair that made it not feel like the vibecoded breakout clone it was. It went way above and beyond the minimum that I've seen so many LLMs do. It was not lazy in the slightest.\n\nIt's a simple test, but this is something everything but something like Opus could handle. There wasn't anything particularly done well, it's just that the whole game was nearly complete in a single shot and it felt like thought was put into the entire game. All I needed was one follow up for customization and a single glitch and it was already what I would consider complete. And this was on a 27B model with Opencode.\n\nThe best way I can describe it, is that it was congruent. Now I just wish I went the Nvidia card route instead of Strix Halo cause the speed isn't great. Maybe 3.7 35B A3B can have some of this magic.\n\n\n\n--- Top Comments ---\n\n\n[55 upvotes] For more speed, use MTP (speculative decoding), a value of 2 or 3 should be good enough. \n\n[29 upvotes] I've been working closely with 27B for the last two weeks, maybe three weeks.  Some observations:  \n1)  <64K context is best for intelligence.  It will \\_still\\_ muddle through tasks at approaching max context on long horizon agentic workloads, but I find it's IQ drops alarmingly past 64K context, and really drops off after 128K.  Telling an agent \"Summarize everything you learned into such-and-such.md\", closing the harness, reopening, and say \"Read such-and-such.md\" is a big key to retaining the intelligence of this model.  \n2) It's one-shot ability on web apps is truly amazing.  For a lot of long horizon tasks where it cannot find a solution, or delivers something that does not work, you're going to have to lead it by the reins and \"vibe code\" it.  For tricky web browser problems, I've even asked it \"Open a browser with API access and watch what I do step by step\" to good effect.  But every time context creeps past 64K or 128K, I have to reset the session as it starts to fall into loops and stupidity.  \n3) It's simply absurdly fun and addictive to have a near-Sonnet class model on our local resources.  I \\_started\\_ with 35B A3B, but the thing is I found it simply did not have en\n\n[18 upvotes] Like I mean it's so popular and good that he didn't even mention QWEN  but I am thinking about it so I guess that's a fact to consider ",
  "transcript_chars": 3106,
  "ingested_at": "2026-05-27T01:30:28.656816+00:00",
  "source": "reddit",
  "yt_meta": {
    "score": 175,
    "upvote_ratio": 0.91,
    "num_comments": 122,
    "author": "Forward_Jackfruit813",
    "is_self": true
  }
}