本地MoE模型智能体编程效率差距明显
AI 总结
Reddit 作者在 Atomic Agent v0.6.10 中，以 Opus 5.5 负责规划，并分别使用 Flint 40B-A2.5B、Ornith 1.5 35B-A3B 和 Nemotron 3.5 Lightning 30B-A3B 并行执行编码任务。Flint 完成 Three.js 任务用时7分36秒，修复6次，Opus 花费0.41美元；Ornith 为9分04秒、14次和0.49美元；Nemotron 则为30分32秒、16次和0.95美元。测试每个模型仅运行一次，未详细评估输出质量，且作者参与开发所用智能体运行时，因此结果仍属初步报告。
深度见解
对比显示，在智能体编程中，模型编辑可靠性和规划返工次数可能比每秒解码速度更重要，但单次运行结果限制了结论的适用范围。
| Three small MoEs dropped within a couple of weeks, so I put all of them in the same seat. In Fusion mode Opus 5.5 plans and reviews, and three workers on the local model write the code in parallel. Only the worker model changes between runs. Same prompt, planner, quant, settings. The task was one prompt: a 20 s Halloween chain reaction in Three.js (flint strikes steel → spark lights a fuse → fuse fires a rocket → rocket knocks a marble down a spiral → marble tips a match into a jack-o'-lantern), follow camera, seamless rewind loop. About 1,000 to 1,700 lines across 6 to 9 files. Setup Time & speed Tokens & cost What stood out Stuff I only saw in the logs Caveats Has anyone run these as sub-agents yet? Does raw tok/s predict wall clock on agentic coding for you, or is it edit success rate like here? Disclosure: I work on Atomic Agent, the open source agent this ran in so ask me anything! submitted by /u/GapNew4766 [link] [comments] |
#Flint 40B-A2.5B#Ornith 1.5 35B-A3B#Nemotron 3.5 Lightning 30B-A3B#Opus 5.5#Atomic Agent v0.6.10#Three.js#llama.cpp#OpenRouter#RTX PRO 6000 Blackwell 96 GB