Independent evaluator Artificial Analysis announced on X on November 4 that its six Capability Indexes (Finance & Accounting, Strategy & Ops, Legal, Healthcare & Medical, Engineering, Economics) are now v2.0, aligned with Intelligence Index v5.0 evaluations and weighting Non-Hallucination and Agentic Tool Use more heavily. Across the indexes, HLE becomes HLE-Diamond, AA-Omniscience moves to v1.1 and GDPval-AA is removed; Engineering gains a new Science capability. Per Artificial Analysis, Claude Opus 5.5 (max) leads all six, with GPT-6 Astra (max) second in Finance & Accounting, Legal and Engineering. Among open-weights models, Kimi K3.1 Pro (weights not yet released) leads all six at #5 to #8.
Key Takeaways
- ✓The six indexes map O*NET occupation tasks to representative benchmarks, weighted by how often each capability appears in that occupation (methodology page)
- ✓Common changes: HLE becomes HLE-Diamond, AA-Omniscience moves to v1.1, and GDPval-AA is dropped from Agentic Knowledge Work (now AA-Briefcase v1.1)
- ✓Non-Hallucination weight rises to 15% in Finance & Accounting and Legal; Agentic Tool Use (AutomationBench-AA) is 35% of Strategy & Ops, its largest component
- ✓Engineering adds Science (20%, CritPt v2 Hard Subset plus Terminal-Bench-Science 0.1) and FrontierCode 2.0 under Agentic Coding; Economics swaps AA-LCR for GDP.pdf
- ✓Results per Artificial Analysis: Claude Opus 5.5 (max) is #1 in all six; among open weights, Kimi K3.1 Pro leads all six, MiniMax-M3.1-Flash leads Strategy & Ops (#10) and DeepSeek V4.1 Flash 1017 (max) leads Healthcare & Medical (#12)
Key Decision Metrics at a Glance
Turn your technical choice into a development budget
Compare 40 dev plans & simulate token costs vs $20/mo subscriptions
Project Links & Resources
Direct AccessIn-Depth Technical Analysis
Background and pain point
A general intelligence score rarely tells you whether a model fits your industry. Artificial Analysis built its Capability Indexes for that: tasks from O*NET occupations are mapped to representative benchmarks and weighted by how often each capability appears in that job. On November 4 it announced v2.0 of all six indexes, aligned with the Intelligence Index v5.0 evaluations.
How it works
The theme is more weight on not fabricating and on real tool use. Per the methodology page, Finance & Accounting is AA-Briefcase v1.1 30%, AA-Omniscience business knowledge 25%, HLE-Diamond 15%, Non-Hallucination 15%, AutomationBench-AA 10% and GDP.pdf 5%; Agentic Tool Use is 35% of Strategy & Ops. GDPval-AA is removed everywhere; Engineering adds Science (20%, from CritPt v2 Hard Subset and Terminal-Bench-Science 0.1) and uses Terminal-Bench 4.0 plus FrontierCode 2.0 for Agentic Coding; Economics replaces AA-LCR with GDP.pdf.
Benchmarks
Per Artificial Analysis, Claude Opus 5.5 (max) ranks first in all six indexes, and GPT-6 Astra (max) is second in Finance & Accounting, Legal and Engineering. Among open-weights models, Kimi K3.1 Pro (weights not yet released) leads all six at #5 to #8; MiniMax-M3.1-Flash is #10 in Strategy & Ops and DeepSeek V4.1 Flash 1017 (max) is #12 in Healthcare & Medical. The exact scores are in the announcement image; this article does not restate unverified numbers.
Getting started
When choosing a model for a vertical, start with that industry index rather than the overall leaderboard, then check the components you care about most, such as Non-Hallucination for finance and legal or AutomationBench-AA for operations automation. v2.0 changes components and weights, so scores are not directly comparable with v1.x. The methodology page lists every component and weight.
Benchmark side-by-side against alternatives, or calculate monthly token cost vs subscription break-even.
Discussion & Comments
0Sign in to join the discussion
Connect with AI developers to exchange benchmark insights.