Atomic Agent

Headlines · 3

1. 2d
   10 coding agents tested on one local Qwen 3.8 27B

   A Reddit user compared 10 coding agents using the same Qwen 3.8 27B Q4 model through llama.cpp on a MacBook Pro M5 Max with 64 GB of memory. Across five trap-containing tasks, every agent passed four or five tasks, while token consumption, completion time, cache reuse, and network behavior varied substantially; Pi used the fewest median tokens, while Qwen Code used the most. Codex CLI, Cline, OpenCode, and goose attempted an internet connection on every run, although the sandbox blocked those requests.

   r/LocalLLaMA · 🔥 1
2. 6d
   Opus planning with local Qwen coding cuts cost but slows builds

   Reddit user u/GapNew4766 built the same five-level pixel platformer twice on a MacBook Pro M5 Max using Atomic Agent. In the self-reported runs, Opus 5.5 alone cost $2.52 and took 16 minutes, while Atomic Fusion used Opus 5.5 for planning and review with three local Qwen 3.8 27B workers, cost $0.62 in cloud usage and took 42 minutes; both games passed nearly the same checklist, at 25/25 and 24/25.

   r/ClaudeAI · 🔥 0
3. 6d
   Blind test compares five self-hosted AI agents on Qwen 3.8 27B

   Reddit user /u/GapNew4766 reported a scripted blind test of OpenCode, goose, Atomic Agent, Hermes and OpenClaw, all running locally on an M5 Max MacBook Pro with 64GB of memory. Each used an uncensored Qwen 3.8 27B model in llama.cpp and completed the same five tasks, including merging contact lists, renaming a function across three files, fixing a bug, counting log errors and converting a receipt PDF into a spreadsheet. All five passed three tasks, while four passed the bug-fix and receipt-conversion tasks; the agent-to-label mapping remained hidden at publication.

   r/MachineLearning · 🔥 0

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