 | 27B Dense vs. 35B-A3B MoE): - Dense still holds the crown: It still wins out on most tasks overall. - The gap is closing: In 7 out of 10 benchmarks, the MoE model is quietly creeping up and closing the distance. - Coding is getting a massive boost: MoE is making serious strides here. For example, the dense model's lead on the SWE-bench Multilingual benchmark dropped from +9.0 down to just +4.1. - The one weird outlier: Terminal-Bench 2.0. For whatever reason, the dense model absolutely pulled ahead here, widening its lead from +1.1 to a massive +7.8. TL;DR: Dense is still technically better, but MoE is catching up fast—especially for coding. If you're running on 24GB VRAM and want massive context windows, the trade-off for MoE is looking better than ever right now. Thoughts? Anyone tested the 256k context on the MoE yet? More details. Check more details in the link: https://x.com/i/status/2047004358500614152 [link] [comments] |
Dense vs. MoE gap is shrinking fast with the 3.6-27B release
Reddit r/LocalLLaMA / 4/23/2026
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Key Points
- The article argues that the performance gap between dense models and MoE (mixture-of-experts) models is shrinking rapidly with the recent 3.6–27B release.
- Despite MoE closing the distance on most evaluations, dense models still generally lead overall across tasks.
- MoE appears to be making particularly large gains in coding benchmarks, with the dense model’s advantage on SWE-bench Multilingual narrowing significantly.
- The only notable exception is Terminal-Bench 2.0, where the dense model’s lead widens substantially.
- For users limited to around 24GB VRAM and seeking very large context windows, the trade-offs increasingly favor MoE according to the reported results.
