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Tasks that have already beaten a model

Every task below was run under gate 5 before it was listed, and carries the pass rate that round measured. Open one to see which model failed it and by how much.

Featured measurement

58%

7 of 12 trials

Rebuild a settlement ledger against withholding mints

Software engineering · medium tier · python

A venue settles trades against quote pools, and the ledger has to be rebuilt from state so it can be reconciled against the chain. Some quote assets are tokens whose mints withhold part of every transfer and do not publish their terms, so the terms have to be inferred from the transfers that were made and what was kept out of them.

What each model did
  • GPT-6 AstraTerminus 24 of 4
  • Claude Fable 5.1Terminus 23 of 4
  • GPT-5.3 CodexCodex CLI0 of 4

GPT-6 Astra passed 4 of 4. GPT-5.3 Codex passed 0 of 4. The headline above reports both of them as the same task, which is why every row in the catalogue opens onto its own breakdown.

Open the full breakdown
What a licence buys

The set, and the evidence it was measured with

The graded task
Its environment and verifier images, pinned by digest, exactly as they were run.
The trial record
Every attempt behind the figures beside this, the ones that errored included.
What stays with us
The instruction, the tests and the reference solution. A measurement you can read the answer to has stopped being one.
The catalogue

Each card carries the rate its round measured and the cells behind it. Open one for the full table, the declared tier and what a licence includes.

 

A wall panel of small squares, a few of them lit, standing on a laboratory bench
How a rate is produced

One cell per agent and model, the same attempts in each, every trial recorded. A rate with no matrix behind it is an opinion about a model.

The programme

11 benchmark families we build sets for

A family is a suite built to order, and most of them draw on several of the categories below at once. Tell us which one you need and we will scope it against the capability you are trying to measure.

Commission a set
  1. 01

    LongHorizon FrontierSWE

    Multi-hour software engineering on real repositories, where the work spans many files and the agent has to hold a plan across hundreds of turns.

  2. 02

    LongHorizon SWE Marathon

    The same shape taken further: sessions long enough that context management and recovery from a wrong turn are themselves what is being measured.

  3. 03

    TB Frontier Science

    Terminal-native scientific computing: data reduction, numerical pipelines, and whether a result reproduces rather than whether it looks plausible.

  4. 04

    Terminal-Bench 3 and 4

    The current Terminal-Bench generations, run under this platform's isolation and scoring rather than on an author's laptop.

  5. 05

    Agent Safety

    Utility and safety as two dimensions of one checkout, so an attempt that does the work and breaks a stated constraint fails rather than half-passing.

  6. 06

    LongHorizon KnowledgeWork

    Knowledge work rather than code, over long horizons: reconciliation against a written policy corpus, and reports somebody is accountable for.

  7. 07

    Legacy Code Migration

    Moving an old codebase forward, where the test suite is the only specification and the framework underneath it has changed since it was written.

  8. 08

    Long-Horizon OSWorld 2

    Desktop work through a GUI, where the state the agent has to reason about is on a screen rather than in a file it can read.

  9. 09

    NL2Repo Samples

    A whole repository from a natural-language brief, graded on what it does rather than on how it reads.

  10. 10

    Multilingual SWE-Bench

    The SWE-Bench shape outside Python, where the toolchain and the build system are part of the task rather than scenery.

  11. 11

    CyberRL Samples

    Offensive and defensive security work under isolation, graded on the outcome and on what the agent was not permitted to touch.

Economically valuable work

The 44 GDPval occupations, and we work in them too

GDPval names the occupations behind the nine sectors that each carry more than five percent of US GDP. We author and grade sets against them, and work of this kind is already in the catalogue above: statutory withholding and input-credit reconciliation is accountants’ work, and a payout run that has to balance is an analyst’s.

Ask about an occupation
  1. Real estate, rental and leasing

    13.8% of GDP
    • Property, real estate and community association managers
    • Counter and rental clerks
    • Real estate sales agents
    • Real estate brokers
    • Concierges
  2. Government

    11.3% of GDP
    • Compliance officers
    • Administrative services managers
    • Child, family and school social workers
    • First-line supervisors of police and detectives
    • Recreation workers
  3. Manufacturing

    10.0% of GDP
    • First-line supervisors of production and operating workers
    • Buyers and purchasing agents
    • Shipping, receiving and inventory clerks
    • Industrial engineers
    • Mechanical engineers
  4. Professional, scientific and technical services

    8.1% of GDP
    • Software developers
    • Lawyers
    • Accountants and auditors
    • Computer and information systems managers
    • Project management specialists
  5. Health care and social assistance

    7.6% of GDP
    • Registered nurses
    • First-line supervisors of office and administrative support workers
    • Medical and health services managers
    • Nurse practitioners
    • Medical secretaries and administrative assistants
  6. Finance and insurance

    7.4% of GDP
    • Financial managers
    • Customer service representatives
    • Securities, commodities and financial services sales agents
    • Personal financial advisors
    • Financial and investment analysts
  7. Retail trade

    6.3% of GDP
    • General and operations managers
    • First-line supervisors of retail sales workers
    • Pharmacists
    • Private detectives and investigators
  8. Wholesale trade

    5.8% of GDP
    • Sales representatives, wholesale and manufacturing, except technical and scientific products
    • Sales managers
    • Sales representatives, wholesale and manufacturing, technical and scientific products
    • First-line supervisors of non-retail sales workers
    • Order clerks
  9. Information

    5.4% of GDP
    • Producers and directors
    • Editors
    • News analysts, reporters and journalists
    • Audio and video technicians
    • Film and video editors

Sectors and occupations as published in GDPval (OpenAI, arXiv 2510.04374), with the GDP shares it reports. The list is theirs; the measurement on this site is ours, and no figure on this page comes from their benchmark.

Categories

What a set can be built in

Each category carries its own artifact contract, base image and resource ceiling, so a set starts from authoring rather than from plumbing. Where a category has finer grain it is listed beside it; most do not, and a set is then scoped against the category itself.

  • Data processing

    in the catalogue
    • Entity matching
    • Data contract
  • Software engineering

    in the catalogue
    • Long context
    • Tool specific
    • API integration
    • Database interaction
    • UI building
    • Issue resolution
    • Marathon
  • Local cloud emulation

    in the catalogue
  • Security

    in the catalogue
  • Cybersecurity

  • Finance and taxation

    in the catalogue
  • Build and dependency management

  • Data science and reporting

  • Debugging

  • Games

  • Hardware

  • Data and infrastructure operations

  • Machine learning

    • Tabular modelling
    • Time series
  • Audio and media data engineering

  • Payroll and compliance

  • Scientific computing

    • Terminal-Bench-Science
  • System administration

Next

Tell us the capability you need measured, and we will scope a set against it

Asking for a task that is in the catalogue gets you the graded set, its images pinned by digest and the trial record behind the figures on its page. Asking for one that is not gets you a scope and a schedule, in the category or the family it belongs to.

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