{
  "video_id": "reddit_1u8pycz",
  "channel_slug": "ClaudeAI",
  "channel_handle": "r/ClaudeAI",
  "title": "GLM 5.2 via Claude Code is the first non-Claude model that feels close to Opus",
  "url": "https://www.reddit.com/r/ClaudeAI/comments/1u8pycz/glm_52_via_claude_code_is_the_first_nonclaude/",
  "external_url": null,
  "upload_date": "20260617",
  "published_at": "2026-06-17T23:19:50+00:00",
  "transcript": "I’ve been using GLM 5.2 with Claude Code through its Anthropic-compatible API endpoint. I’ve tested it on various projects, including but not limited to database development, backend payment API work, backend and frontend debugging, Laravel web development, and React frontend work.\n\nFor the first time, I can confidently say that, in my experience, with thinking set to \"max\" it seems on par with Opus 4.8 using \"extra-high\" reasoning.\n\nYes, this is anecdotal and I have no definitive benchmarks to backup my claim. That said, I’m a senior developer with three Claude Max subscriptions. I love Claude, use it heavily, and am not trying to knock Anthropic or imply that I'm replacing it.\n\nI also use other models, such as DeepSeek V4 Pro (more than 2 billion tokens in the past few months) with the Claude Code harness. Specifically, I normally use DeepSeek as an implementer and found it useful in that limited role. I would roughly compare it to Sonnet 4.6. But GLM 5.2 is the first model I’ve used where I genuinely felt something was approaching Claude’s top-tier coding ability as well as planning/drafting specs, etc.\n\nBefore this gets downvoted by the Anthropic trolls: yes, as mentioned above, this is anecdotal. There is also the obvious issue of the model being Chinese, which is another discussion in itself with respect to data sensitivity and other related issues.\n\nThe point of this post is simply to make users aware that there may now be open-source or lower-cost models approaching, or in some cases reaching, Claude-level usefulness for real development workflows. And the current U.S. policy environment (Fable) is not exactly helping domestic models stay comfortably ahead of foreign competition.\n\n\n\n--- Top Comments ---\n\n\n[48 upvotes] Well, it *was* rated extraordinarily high compared to other open models on Artificial Analysis, near the same family as GPT-5.5, Opus 4.7, and Opus 4.8. It's definitely part of the next generation of Chinese models (funny how each generation is just a few months these days). \n\nFrom a non-American perspective, so less sensitive about the model being Chinese (because you guys collected and sell my data anyway). The enormous prices of Anthropic models are increasingly off-putting, especially as gains are often lower than costs and it's easier and cheaper to hire two guys using GLM rather than having one guy using Opus. At least OpenAI and Codex are still floating insanely subsidized plans, or I'd have moved primarily to the Chinese stack already.\n\n[15 upvotes] the part that surprises me is GLM holding up on planning/spec drafting, not just implementing. most of the cheaper models i've tried fall apart the moment the task needs them to hold a whole architecture in their head, they're fine as code monkeys but can't reason about tradeoffs.\n\nif it's actually matching opus on the planning side that's the real story here. how does it do over long sessions, does context degrade?\n\n[11 upvotes] They gonna ban you for posting this😭😭",
  "transcript_chars": 2995,
  "ingested_at": "2026-06-18T01:30:28.389377+00:00",
  "source": "reddit",
  "yt_meta": {
    "score": 90,
    "upvote_ratio": 0.91,
    "num_comments": 28,
    "author": "nseavia71501",
    "is_self": true
  }
}