{"type":"post","id":"artificial-analysis-publishes-per-benchmark-results-with-the-03859f","slug":"artificial-analysis-publishes-per-benchmark-results-with-the-03859f","title":"Artificial Analysis publishes per-benchmark results with the index and documents task construction, scoring, and model handling in its methodology .","description":"Thesis: A benchmark aggregate becomes more useful when its component tasks and scoring rules are inspectable, but transparency alone does not establish that its mix matches a team's deployment needs.","retrieval_nugget":"Thesis: A benchmark aggregate becomes more useful when its component tasks and scoring rules are inspectable, but transparency alone does not establish that its mix matches a team's deployment needs.","published_at":"2026-10-14","updated_at":"2026-10-14","record_date":"2026-10-14","date_kind":"published_at","topics":[],"source_urls":["https://artificialanalysis.ai/methodology/decision-index"],"schema_version":"newruntime-agent-readable-v0.2","stable_id":"post:artificial-analysis-publishes-per-benchmark-results-with-the-03859f","status":"published","visuals":[],"editorial_provenance":{"schema_version":"newruntime-editorial-copy-v1","content_status":"source_grounded_final","final_copy_sha256":"sha256:6eaff04470e7b1590e6ba533ed90a38365c5e575c54fab1e8e5df3d50bb41218","reviewed_at":"2026-10-14T02:01:43.422Z","source_evidence_count":1,"verified_claim_count":3,"site_analysis_schema_version":"newruntime-site-analysis-v1","site_object_kind":"field_note","observed_fact_count":3,"implication_count":1,"watch_condition_count":1,"related_record_count":0},"analysis":{"schema_version":"newruntime-site-analysis-v1","object_kind":"field_note","thesis":"A benchmark aggregate becomes more useful when its component tasks and scoring rules are inspectable, but transparency alone does not establish that its mix matches a team's deployment needs.","observed_facts":[{"text":"Artificial Analysis says the Decision Index is a weighted average of four evaluations, each assigned 25%: AA-Omniscience-Decision, HLE-MultiChoice, When2Call, and WildGuardTest.","source_urls":["https://artificialanalysis.ai/methodology/decision-index"]},{"text":"The methodology specifies that AA-Omniscience-Decision contains 500 private questions with four answer choices plus “I don't know,” and splits its contribution between accuracy and non-hallucination rate.","source_urls":["https://artificialanalysis.ai/methodology/decision-index"]},{"text":"It says HLE-MultiChoice uses 513 text-only questions from Humanity's Last Exam.","source_urls":["https://artificialanalysis.ai/methodology/decision-index"]}],"mechanism":"The score combines distinct capabilities—knowledge and hallucination, reasoning, tool calling, and classification—under fixed equal weights. The page also describes differences in response handling: decision models return choices and probabilities, while language models receive a fixed prompt and are constrained to structured outputs.","why_now":"Teams comparing model endpoints need to know which tasks and scoring conventions shape a benchmark before using it to shortlist candidates.","implications":["Teams can use the index as an initial shortlist, then test leading candidates against their own labels, traffic, and error costs."],"evidence_boundary":"The available source documents the benchmark's composition and stated scoring procedure; it does not establish how representative the tasks are of a particular production workload or whether the ranking predicts outcomes there.","watch_conditions":["Watch for teams publishing evaluations that compare the index's shortlist with results on their own labeled workloads and error-cost profiles."],"related_records":[],"new_branch_reason":"No prior New Runtime record is supplied for this exact Decision Index methodology disclosure; it warrants a distinct record focused on benchmark composition and score interpretation."},"editor":{"role":"editor","name":"Andrey Reshetnikov","profile":"https://newruntime.com/owner-profile.md","profile_json":"https://newruntime.com/owner-profile.json","same_as":["https://www.linkedin.com/in/reshetnikov1/","https://t.me/lapetuse"]},"routes":{"html":"https://newruntime.com/posts/artificial-analysis-publishes-per-benchmark-results-with-the-03859f/","markdown":"https://newruntime.com/posts/artificial-analysis-publishes-per-benchmark-results-with-the-03859f.md","json":"https://newruntime.com/posts/artificial-analysis-publishes-per-benchmark-results-with-the-03859f.json"},"next_reads":[{"type":"collection","path":"/posts/","url":"https://newruntime.com/posts/","title":"Field Notes","reason":"Open the latest editorial analysis.","media_type":"text/html","json_url":"https://newruntime.com/posts.json"},{"type":"collection","path":"/source-ledger.json","url":"https://newruntime.com/source-ledger.json","title":"Source Ledger","reason":"Inspect the public source evidence graph.","media_type":"application/json"}]}