{
  "video_id": "reddit_1u0yo32",
  "channel_slug": "LocalLLaMA",
  "channel_handle": "r/LocalLLaMA",
  "title": "Have we reached the point where open-source LLMs are “just good enough”?",
  "url": "https://www.reddit.com/r/LocalLLaMA/comments/1u0yo32/have_we_reached_the_point_where_opensource_llms/",
  "external_url": null,
  "upload_date": "20260609",
  "published_at": "2026-06-09T08:02:32+00:00",
  "transcript": "The question I’m asking myself is whether open-source LLMs are now “**just good enough**” to meet 95% of requirements. I know, of course, that they still need to and will get even better, but where does the added value of the remaining 5% come from?\n\n* a) Better answer quality? Okay, but does that justify the extra cost?\n* b) Cleaner automated loops? Do the extra costs justify the effort of manual interventions to produce the same or similar quality?\n* c) Reduced risk of facing internal/external criticism for betting on the wrong/slower horse (since the prevailing opinion is that only the first ones are the best)\n* d) Even greater productivity? Okay, but does this justify the additional costs?\n* e) General risk management: if errors occur, can we protect ourselves, since we’ve chosen the best (OpenAI, Anthropic, Google, etc.) anyway?\n* f) ???\n\nAs I said, I’m primarily concerned here with **cost-benefit arguments** (**that we want to advance technically goes without saying**) and with other opinions … (to better position ourselves internally)\n\n**What do you think?**\n\n\n\n--- Top Comments ---\n\n\n[67 upvotes] I've tried mini max 2.7, deepseek v4 flash, qwen 122b, coder next, qwen 27b, Gemma 31b. The best one without question is still qwen 3.6 27b. I have dual rtx pro 6000s. Regretting buying the second one lol\n\nBut to answer your question. No. They don't have near the amount of parameters.. any one of them.. to read your mind and know exactly what you want like the big models do. They do small tasks great but if it needs to go into like four or five different files it's going to get confused no matter which model that you use whereas if opus and GPT absolutely no problem going into like 30 or 40 at a time.\n\nYou say 95% but I don't think any of these models even make it to like 50 or 60%. Even with extensive skills rules and prompting it's like an 70-80% in terms of trusting the code. With the big api models you do something and you know it thought of like 50 different edge cases. With the small models you know it maybe thought of one or two. It leaves a constant uneasy feeling for anybody who's serious about production level code.\n\nFrontend: Gemma 4 31b\nBackend: Qwen 3.6 27b\nAll around: Qwen 3.6 27b\n\nTop list:\nQwen 27b\nDeepseek flash\nMinimax\nGemma\nCoder next\nQwen 122b\n\nSame prompt, same\n\n[24 upvotes] Writing and creative topics:\n- Gemma 4 26B-A4B\n- Gemma 4 31B\n\n\nScience, engineering, vision, tool use:\n- Qwen3.6 35B A3B\n- Qwen3.6 27B\n\n\nConsidering the quality and speed of these models (mainly the MoE), in my case they have completely replaced the most powerful models currently available.\n\n\nThey aren't as intelligent, but they are almost as usable.\n\n[14 upvotes] have been using claude opus to act as a director and let it whip a bunch of grunt LLMs. Minimax, Qwen27b etc\n\nno huge frameworks or \"hey look what i made\".. opus just uses pydantic\\_ai to form a very simple toolcall loop for the grunts.\n\nthis has worked well, keeps the opus usage very low.\n\n[9 upvotes] Never used the cloud models so can't tell about that.\n\nMy humble experience with llama.cpp+pi agent+Qwen3.6-27B+3090 24Go VRAM and a codebase of a bit more than 130k is:\n\nif you have a workflow where you first draft a PLAN.md then make the model review it, update it with a few iterations adding comments in it like `<!-- USER: keep this file untouched -->` and implement it Phase by Phase in a git repository it works pretty fine and you can achieve huge amount of work be it refactoring, fixing, adding features...\n\nBeen doing that for only two weeks when i finally went the agentic way in a sandbox and i'm impressed by what i can do fully local.",
  "transcript_chars": 3656,
  "ingested_at": "2026-06-09T13:30:11.296029+00:00",
  "source": "reddit",
  "yt_meta": {
    "score": 55,
    "upvote_ratio": 0.85,
    "num_comments": 86,
    "author": "AdDizzy8160",
    "is_self": true
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}