Qwen 3.8 27B Q5 vs Qwen 3.8 Next Q3_S for document analysis

I have an app that processes ~500 different documents every day. An agent analyzes them, sorts them, tags them, extracts various legal nuances, creates descriptions, etc. So far I've been using Qwen 3.8 27B Q5 with a 150K context window, but I'm wondering whether I should switch to Qwen 3.8 Next Q3_S, since it has much more knowledge and could extract data much better than the 27B. However, I'm hesitant because it's a MoE model and Q3 is quite a low quantization, so I'm worried the results could end up being worse. Everything run on 64 GB of RAM and an R9700. submitted by /u/RaDDaKKa [link] [comments]

unsloth/Qwen3.8-Flash-Next-GGUF is being updated
R9V Update: Created and adopted KVA projections based on Deepseek V4.1 Flash + HySparse2/MiMo-V3 for Qwen3.8 Flash Next. This is a game changer for models that don't natively implement it. 1.45-1.85x speedup in prefill to 3k+ at a small deficit to perplexity. [2x R9700, 128GB DDR5]
Two open-weights releases: Victoria (Qwen3.8-Flash-Next with 44% of experts cut, 70% Terminal-Bench 2.1, GGUF included) and Maple (a Canada-first fine-tune)
Ugh I didn't want to post this... Back to Qwen3.8 27B

Source: r/LocalLLaMA | 2026-10-11

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