It does really well on "AA-Omniscience Non-Hallucination Rate", far higher than DeepSeek, GPT 5.5 or Fable. I really like that benchmark because it's one of the few benchmarks that allows LLMs to elect not to answer if they are unsure and punishes them for trying to bullshit their way through the benchmark
by gertlabs
0 subcomment
On our multi-agent coding and reasoning evaluations, GLM 5.2 is the first model we've tested that crossed the threshold of being on par with or better than Opus 4.6 (although as usual, we have GLM 5.2 and most other Chinese models a bit below most other benchmarks with test methodologies that are more vulnerable to benchmaxxing).
It's always nice to see how open source models growing, hope we will have good performance with lower tier hardware some day.
by theturtletalks
1 subcomments
I want to trust their benchmarks but when they have Muse Spark over GPT-5.5, it gives me pause.
by hemkeshr
1 subcomments
Local models are already useful today. The next milestone is getting this level of performance onto truly affordable hardware.
by ttoinou
0 subcomment
Would be interesting to see if we can make this model smaller with REAP + unsloth dynamic quant. It might become 4x cheaper to run for similar quality output
by fcpk
0 subcomment
tangent question: Claude code seems to be very much loved and suggested by most major Chinese LLM using the env vars to change the server. that however means you lose a lot of anthropic tools like auto mode, running shells, monitors/crons. is there a way to get those with non anthropic plans?
by linzhangrun
0 subcomment
Coding Plan is completely unavailable
by DeathArrow
1 subcomments
One or two more releases and they will reach Fable level.
by sourcecodeplz
0 subcomment
still quite verbose at 140m output tokens, but this is on max thinking. high should do better.
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