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Anubis OSS, an Apple Silicon Mac app for benchmarking local LLMs, now supports direct model downloads from the UI via a 'Browse Models' button that pulls from ollama.com library. The developer is seeking testers to confirm installation and functionality.
This paper proposes A-LEMS, a framework that redefines AI energy accounting from per-inference to Energy per Successful Goal (EpG), and introduces the Orchestration Overhead Index (OOI) to measure energy costs of multi-step orchestration in agentic systems. Empirical results show agentic workflows consume 4.33× higher mean energy per goal than linear baselines, but OOI can invert for tool-augmented tasks, demonstrating goal-level accounting is necessary.
1rok is a TypeScript framework that enables running multi-agent portfolio construction pipelines across multiple LLM providers to benchmark their performance on financial tasks like stock selection and position sizing.
Shares early benchmark scores and evaluation metrics for an open-weight model stack run on a single AMD MI300X, noting competitive performance against closed-source alternatives.
A user benchmarks three Qwen models (Qwen3.5-27B dense, Qwen3.5-122B-A10B MoE, Qwen3.6-35B-A3B MoE) on 4x RTX 3090 GPUs under real agentic workloads, finding that MoE models consistently underperform the dense 27B at following strict global rules despite speed advantages, with the Qwen3.6-35B leading in generation throughput.