RLCD

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1. 4d
   Oumi Investigates Jev’s Likely Architecture and Training

   Oumi researchers used behavioral probes, benchmark results and serving profiles to estimate which model TypeSafe’s Jev may be based on and how it may have been trained and served. Without insider knowledge, they say Jev is likely built on Qwen 3.5 or 3.6 in a 35B-A3B configuration, with a tokenizer merging Qwen and GPT-OSS. They also speculate that its RLCD method uses soft-label cross-entropy on synthetic data rather than PPO or GRPO. For serving, they propose tree batching and either a form of sparse attention or deployment on two GPUs with the prefill split between them.

   r/LocalLLaMA · 🔥 0

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