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Qwen3.8-27B-antislop, RL’d against slop, top4 on eq bench4

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Based on a feed excerpt; full article content has not been acquired. Source evidence retrieved 17/10/2026, 09:47:26 UTC.

Briefings

A modified version of Qwen3.8-27B, trained with RL against 'slop' using Meta's RL-XAR style, achieved top-4 performance on the EQ benchmark in BF16+MXFP4 format. The model was submitted to the r/LocalLLaMA subreddit by user Mysterious_Hearing14, though specific training details and evaluation metrics beyond the top-4 ranking are not fully disclosed.

Key points

• The model Qwen3.8-27B-antislop was trained using Reinforcement Learning from the Human (RL) in the style of RL-XAR by Meta.
• The model achieved top-4 ranking on the EQ benchmark using the BF16+MXFP4 format.

Context

This finding represents a specific instance of model optimization where a Qwen3.8 variant was trained against 'slop' using Meta's RL-XAR style, resulting in improved performance on the EQ benchmark.

Limitations

The evidence is limited to a Reddit post and a Hugging Face submission link. Specific training details, evaluation metrics beyond top-4 ranking, and the model's performance on other benchmarks are not provided.

Generated by Bittrees-hosted qwen35-2b sha256:aaf42c8b7c3c on 25/10/2026, 03:53:46 UTC. Based on publisher-provided feed evidence; may not cover the full original article. Check the source for details.

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