Salience 1 — 9B A 9B multimodal reasoning model, sharpened for code and agentic work — that can see. Vection Labs Weights · Benchmarks · Quickstart · Fast inference · Limitations Abstract Salience 1 (9B) is a dense, 9 billion parameter vision language model built for hard, practical work : writing and debugging real code, driving tools and agents, multi step mathematical reasoning, and visual understanding over images and video — inside a single model with a context window of up to 1M tokens . It is the successor of Maestro1 9B, engineered around a single goal: push the axis users ask for most — code and agentic/tool use — without giving up the deep reasoning, vision, and million token context the family is known for. It is designed for people who care less about chat pleasantries and more about whether the model can do the thing : ship the function, find the bug, call the right tool, read the diagram, finish the proof. Highlights Code & agentic first. Built with a coding/DevOps donor on top of a reasoning core; tuned to produce runnable code and well formed tool calls. Reasoning that shows its work. Structured, inspectable chains of thought for math, logic, code. Genuinely multimo…
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