aiqbench analysis
Fastino's GLiNER2.5-Decide addresses a critical bottleneck in AI agent pipelines by providing a deterministic, non-generative model for high-stakes routing and guardrail decisions. By outputting structured probabilities and constraint-feasibility metadata without generating tokens, it enables reliable tool selection and safety verification even in air-gapped or CPU-only environments. This specialized approach offers a robust alternative to general-purpose LLMs for operational judgment calls where hallucination-free outputs are mandatory.
Fastino Releases GLiNER2.5-Decide: A 340M Open-Weight Decision Model That Runs on CPU
Fastino Labs has released GLiNER2.5-Decide, a 340M-parameter open-weight decision model. It takes text and a schema of typed questions and returns structured answers. Each answer comes with a probability distribution, a confidence score, and constraint-feasibility metadata. It targets the frequent judgment calls inside agent pipelines: routing, triage, tool selection, and guardrails. Is it deployable? Yes, […] The post Fastino Releases GLiNER2.5-Decide: A 340M Open-Weight Decision Model That Runs on CPU appeared first on MarkTechPost.
Fastino Labs has released GLiNER2.5-Decide, a 340M-parameter open-weight decision model. It takes text and a schema of typed questions and returns structured answers. Each answer comes with a probability distribution, a confidence score, and constraint-feasibility metadata. It targets the frequent judgment calls inside agent pipelines: routing, triage, tool selection, and guardrails. Is it deployable? Yes, the weights ship under Apache 2.0 and install with pip install gliner2. They run on CPU, GPU,…
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