The Intelligence Index — Latest AI Models Compared
    LATEST VERSIONS ONLY · EVERY FIELD FILLED · ONE LIVE REFERENCE

    Every frontier model, side by side.

    The newest release from every major AI lab — specs, pricing, abstract-reasoning, science, coding and agentic scores, a value ranking and a cybersecurity posture index. Click any column header to sort.

    Compare models →Cybersecurity
    latest models across labs
    #1 on the independent Intelligence Index
    best value (Index per blended $)
    01 — LABS

    Who’s building what

    Ten labs define the frontier and its open-weight tail.

    02 — DIRECTORY

    Every latest model

    One row per current model — older generations are dropped. AA Index = Artificial Analysis Intelligence Index v4.3.2. Prices per million tokens. Value = Index ÷ blended price (3 parts input : 1 part output). Every cell is filled; EST marks our estimate where a lab hasn’t published a comparable figure.

    03 — HEAD TO HEAD

    Compare up to three models

    Pick models to see every spec side by side. Best value in each row is highlighted green.

    04 — BENCHMARKS

    Reasoning, science & agentic coding

    No certified AGI test exists; these are the closest public proxies.

    Oct 14, 2026: Gemini 4 Argon (GA Oct 13) scores 52.6 on the Intelligence Index — level with GPT-6 Astra and Claude Fable 5.1, behind Claude Opus 5.5 (57.6, #1) and Sonnet 5.5 (56.0). Index scores use the v4.3.2 scale and aren’t comparable with earlier editions. Vendor launch tables run higher than independent runs. Bars labelled “est.” are our estimates, not published results.

    Artificial Analysis Intelligence Index

    Composite of 10 evals: reasoning, knowledge, coding, math, agentic work.

    Terminal-Bench 4.0 — agentic terminal tasks (%)

    Multi-step software, sysadmin and data tasks, mostly vendor-reported.

    ARC-AGI-2 — novel abstract reasoning (%)

    Puzzles that resist memorization; average human ≈ 66%.

    GPQA Diamond — graduate-level science (%)

    PhD-level, Google-proof multiple-choice questions.

    SWE-bench — real GitHub issue fixing (%)

    Resolving real software issues end to end.

    05 — CYBERSECURITY

    Cybersecurity posture index

    Reading this table: no certified AI cybersecurity leaderboard exists. Ratings are a directional synthesis of lab system cards and third-party research, not a head-to-head score. Baseline: LLMs suggest insecure code in about 1 of 3 completions and often comply with attack-assistance requests absent safeguards. Models without enough red-team data (Muse, Kimi, MiMo, Qwen, Mistral) are left unrated.
    ModelSecure codeInjection resist.Attack refusalGatingNotes
    06 — METHOD

    How this page is built

    01
    Public sources

    Lab release notes, system cards and public leaderboards.

    02
    Monthly refresh

    New releases replace older versions of the same model line.

    03
    No single “best”

    Rankings shift by task and reasoning effort.

    04
    Estimates marked

    Gaps are filled with clearly badged estimates, never silently.

    Independent reference page. Not affiliated with any lab named. Trademarks belong to their owners. Figures are best-effort and may lag official leaderboards.
    Omkar Nath Nandi

    Omkar Nath Nandi

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