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Qwen2.5 Coder Instruct 32B benchmark scores revealed in independent tests

Independent evaluations of the Qwen2.5 Coder Instruct 32B model have yielded specific benchmark scores. The model achieved 41.7% on GPQA, 63.5% on MMLU-Pro, 3.5% on Humanity's Last Exam, and 29.5% on LiveCodeBench. These results were not self-reported by the model's creators and offer a distinct perspective on its capabilities. AI

IMPACT Provides objective performance data for a specific coding-focused LLM, aiding developers in model selection.

RANK_REASON Independent benchmark results for an open-source LLM. [lever_c_demoted from research: ic=1 ai=1.0]

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AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Qwen2.5 Coder Instruct 32B benchmark scores revealed in independent tests

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Independent benchmark results for an open-source LLM. [lever_c_demoted from research: ic=1 ai=1.0]
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  1. Mastodon — mastodon.social TIER_1 English(EN) · opensourceaitech ·

    📊 Qwen2.5 Coder Instruct 32B measured independently: GPQA 41.7%, MMLU-Pro 63.5%, Humanity's Last Exam 3.5%, LiveCodeBench 29.5%. Not a self-report—these raw num

    📊 Qwen2.5 Coder Instruct 32B measured independently: GPQA 41.7%, MMLU-Pro 63.5%, Humanity's Last Exam 3.5%, LiveCodeBench 29.5%. Not a self-report—these raw numbers tell a different story. The full breakdown is right after here. https:// olud.ai/leaderboard.html # LLM # Benchmark…