Development material
Cases are selected for internal development and may have been exposed to the project. Small samples and repeated calls do not establish general performance.
PALO BlueprintBench / Local development study
Local models for source-fidelity review.
Explore how model configurations classify claims against supplied source excerpts. Compare retained responses, processing times and the hardware used to run each test. The advisory agent is intended to challenge draft interpretations before human review.
These tests use the agent prompt and output validator via a local model endpoint. The full agent application workflow was not executed. Model agreement is not ground truth; independent expert adjudication and validation remain pending.
Study limitationsSource fidelity / Model and serving configuration
Filter by configuration and case. Missing and invalid responses remain visible. Numeric sorting is for inspection, not a qualified ranking.
Observed request duration
One row represents a case and a model configuration. Filter to one case when inspecting different configurations. Output caps and prompt identifiers are listed with each result.
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Bars use the maximum visible median as the scale. Different prompts, output lengths, serving settings and hardware affect duration.
Measurement notes
Case-level observations
Scroll horizontally to see all fields.
| Configuration / hardware | Case | Output cap / prompt | Completed / assigned | Contract valid | Not completed / invalid | Median time | Completion tokens | Observed label | Agreement | Evidence |
|---|---|---|---|---|---|---|---|---|---|---|
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Not completed includes failed, incomplete and unrun calls. Invalid counts refer to completed calls that failed contract checks. A missing duration or label is shown as N/A. No energy use, GPU offload or monetary cost is inferred from a local run.
Study design
Results belong to the reported model, prompt, runtime and hardware configuration.
Cases are selected for internal development and may have been exposed to the project. Small samples and repeated calls do not establish general performance.
These tests exercise the agent prompt and output validator via a local model endpoint, not the full agent application workflow. Labels and explanations are model-generated suggestions; matching quotations do not verify their conclusions.
Human expertise, independent adjudication, external custody and measurement validation remain separate requirements.