Aplomb 1: open-weights 5.3B decision model with 1M context, tops 4B class on Decision Index
empiriolabsai · reddit · 2026-10-07
EmpirioLabs released Aplomb 1, an open-weights 5.3B decision model built on Qwen3.5-4B: it reads up to 1M tokens of text/images/video/audio in one request and returns probabilities for tool selection and arguments, letting agents act on confident calls and escalate the rest. It scores 44.86 on Decision Index 0.2.1 (#1 among 4B models) and tops models up to 5.3B on 8 of 38 benchmarks incl. MMLU-Pro, GPQA Diamond, and BBH. A custom inference runtime cuts full 1M-token decision reads to 3s from 111s; the API costs $0.02/1M input tokens with free output and ZDR by default, OpenAI/Anthropic/Gemini-compatible. Weights run in bf16 on 12GB GPU; free for research, personal, and sub-$1M-revenue company use. Training data included public train splits of two of the 38 index benchmarks (WinoGrande, ContractNLI).
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