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GLM-5.3 and Qwen 3.8 27B models tested on SlopCodeBench

New benchmark results for the GLM-5.3 and Qwen 3.8 27B models on the SlopCodeBench have been released. GLM-5.3 achieved a score of 8/17 on a 17-checkpoint subset and 10/30 on a 30-checkpoint subset, tying with Fable 5 and GPT-5.6 Sol on the latter. Qwen 3.8 27B performed less impressively, scoring 3/17 on the 17-checkpoint subset and 4/30 on the 30-checkpoint subset, indicating potential issues with code management and organization when used autonomously. AI

IMPACT These benchmarks provide insights into the coding capabilities of different LLMs, informing developers and researchers about their strengths and weaknesses in handling complex coding tasks.

RANK_REASON The cluster reports benchmark results for AI models on a specific coding task, which falls under AI research.

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AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

GLM-5.3 and Qwen 3.8 27B models tested on SlopCodeBench

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COVERAGE [2]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/corruptbytes ·

    GLM 5.3 SlopCodeBench Results

    <!-- SC_OFF --><div class="md"><p>Howdy once again, I had a request to try out 5.3 on the benchmarks - they're unsaturated so it's a fun test right now! This one was interesting because I accidentally ran it on all 36 problems (rip $200) instead of the 9 i typically do</p> <p>pre…

  2. r/LocalLLaMA TIER_1 English(EN) · /u/corruptbytes ·

    Qwen 3.8 27B SlopCodeBench results

    <!-- SC_OFF --><div class="md"><p>Howdy, I'm back again - running my favorite benchmark (it's still unsaturated for the time being so might as well!)</p> <p>previous runs <a href="https://www.reddit.com/r/LocalLLaMA/comments/1vbtiy7/deepseek_v4_flash_on_slopcodebench/">a</a> <a h…