GLM 5.2 Performance Benchmarks

GLM-5.2 (max) just dropped into the AI rankings like a reality-show contestant who is obviously talented but also arrives wearing a wildly expensive outfit. On paper, the model looks strong: it scores 51 on the Artificial Analysis Intelligence Index, which puts it far above the average in its class, it blasts along at 112 tokens per second, and it can handle a massive 1 million-token context window — basically a huge amount of text at once. But the community? Oh, the community immediately turned this into a messy group chat about trust, bragging rights, and whether this thing ever stops talking.

The biggest applause came from people cheering open models getting closer to the top. One commenter joked that with “one or two more releases” it could hit Fable level, which is basically the AI equivalent of saying, “Cute now, but future champion.” Others were more impressed by a benchmark that rewards models for admitting when they don’t know something instead of confidently making stuff up. That got real love, with one fan practically applauding GLM-5.2 for not trying to “bullshit” its way through hard questions.

But not everyone was buying the party balloons. One camp side-eyed the benchmark rankings altogether, saying results like Muse Spark beating GPT-5.5 made them hesitate. Another recurring gripe: this model is chatty. At 140 million output tokens during testing, some users basically called it the friend who answers a simple question with a podcast. So the verdict is deliciously divided: impressive, fast, and open — but expensive, wordy, and still on trial in the court of comment-section opinion.