Model Releases
3.8-27B has ruined 3.5/3.6-35B’s for me. It’s just *absurdly* superior.
Applied science work, from workflow design, data pipeline, results analysis, article/reports writing and data publishing online. 5 projects I did in the past replicated from start to finish. 3x to 4x
Applied science work, from workflow design, data pipeline, results analysis, article/reports writing and data publishing online. 5 projects I did in the past replicated from start to finish. 3x to 4x more total wall time. Yes, HUGE toll on how much you can do in a day if this was the only model you could use in your laptop. But oh my…the quality of that thing. The stupid level of attention to detail. I have the Z.ai api, so I can compare it with 5.3 and 5.3-flash: The gap between 5.3 (flash and regular) and 3.8-27B is much less, smaller when not plain tiny, than the gap between 3.8-27B and any of the 3.5/3.6-35B-A3B (vanilla, kat, Ornith/tiel, nex-2). Only Ornith came close, but it never matched it. But it’s also spending 22 to 33% less tokens (effort =medium) and less ram footprint, so you get more done without hitting limits,compaction, etc. So yeah, guess I’ll sip more tea, play the piano, whatever. Let that fat bottom Qwen work. submitted by /u/JLeonsarmiento [link] [comments]
Related
- Qwen3.8-Flash-Next-NVFP4 vs Qwen3.8-27B-FP Test Results
- Long Review: Qwen 3.8 27B is VERY good at tapping into it's real-world knowledge. It's 'overthinking' brings it to Sonnet level performance with the potential for Opus level results.
- Kaitchup posted Qwen3.8 27B Benchmarks for quants from Q4 to Q1
- Qwen 3.8 27B, just wanted to say thanks to you guys
Source: r/LocalLLaMA | 2026-09-12