VIDRAFT's Darwin-180B-RSI MoE Model Claims Top Spots on Five Hugging Face Leaderboards

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Korean Pre-AGI startup VIDRAFT has released Darwin-180B-RSI, a 180-billion-parameter mixture-of-experts reasoning model built on Qwen3.8-Flash-Next, in late September 2026. The model uses selective model merging combined with a recursive self-improvement loop, where verified correct outputs are used to retrain the model across multiple iterations. VIDRAFT reports perfect scores on AIME 2026 and HMMT 2026 math benchmarks, along with strong results on GPQA Diamond, MMLU-Pro, and MMMU-Pro, claiming first place on five Hugging Face leaderboards. Despite its large parameter count, the sparse MoE architecture activates only 10 of 512 experts per inference pass, keeping computational costs lower than a comparable dense model. However, all benchmark results are self-reported by VIDRAFT and have not been independently verified by third parties.

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