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Revelo Terminal-Bench 4.0 tasks: samples

Dataset Description

20 sample tasks from Revelo's set of 5,000+ terminal tasks for AI agents.

Each task puts an agent in a Linux container with existing code or data and a written request. The agent must build, repair or finish working software, for example a deadlock model in VHDL, a margin analyzer in Rust or a geological model in C++. A hidden test suite then checks the result in a separate container. The agent never sees the tests, and partial work does not pass.

The tasks cover hardware, science, security, finance and software engineering. Each task gives the agent 4 to 8 hours.

For evaluation only. Please do not use these samples to train models.

The two sample sets

Set Tasks Claude Sonnet 5.5 GPT-6 Luna Hy4 Preview
hard/: frontier models fail most runs 10 13 of 80 runs pass (16%) 13 of 100 runs pass (13%) 3 of 50 runs pass (6%)
solved/: at least one frontier model solves every run 10 80 of 80 runs pass (100%) 55 of 100 runs pass (55%) 22 of 50 runs pass (44%)

A run passes when the held-out verifier gives a reward of 1.

Dataset Structure

Each task is a Harbor task with this layout:

<task>/
β”œβ”€β”€ harbor_task/
β”‚   β”œβ”€β”€ instruction.md      # the task the agent receives
β”‚   β”œβ”€β”€ task.toml           # metadata, resource limits, verifier settings
β”‚   β”œβ”€β”€ environment/        # Dockerfile and starting workspace
β”‚   β”œβ”€β”€ tests/              # held-out verifier, runs in a separate container
β”‚   └── solution/           # expert reference solution
└── rollouts/
    └── <model>/<run>/      # full trajectory, submission, verifier output, reward
  • A senior engineer authors every task. Two independent reviewers check it.
  • Each task includes the expert's reference solution.
  • task.toml explains why the task is hard, how the reference solution works, and what the verifier checks.

Tasks

Hard set

Task Domain Claude Sonnet 5.5 GPT-6 Luna Hy4 Preview
chi-scc-witness Hardware / RTL 3/8 0/10 0/5
charger-rk4-ribbons Science / Physics 1/8 3/10 0/5
citygml-barycentric-meshing Software / Algorithms 2/8 1/10 0/5
coseismic-trapezoid-clipping Science / Earth 1/8 2/10 1/5
flatzinc-blossom-transform Software / Algorithms 0/8 2/10 1/5
imputation-release-audit Science / Biology 0/8 0/10 1/5
margin-transition-reconciliation Software / Data engineering 1/8 0/10 0/5
roster-causal-frontier Software / Frontend 2/8 3/10 0/5
session-joint-transport Science / Math 0/8 1/10 0/5
trial-witness-cover Software / Algorithms 3/8 1/10 0/5

Solved set

Task Domain Claude Sonnet 5.5 GPT-6 Luna Hy4 Preview
atlas-liquidity-sweep Operations / Finance 8/8 9/10 4/5
bridge-causal-certificate Security / Forensics 8/8 1/10 2/5
canonical-phrase-dag Software / Algorithms 8/8 8/10 1/5
hl7-panel-ownership Software / Systems 8/8 2/10 0/5
lectionary-layout-dp Software / Algorithms 8/8 8/10 3/5
lexical-history-incidence Software / Database engineering 8/8 6/10 1/5
meaning-history-minloss Software / Algorithms 8/8 5/10 3/5
mlkem-anchored-moments Security / Cryptography 8/8 8/10 4/5
report-lock-compositor Software / Algorithms 8/8 1/10 1/5
rna-velocity-cdf Science / Biology 8/8 7/10 3/5

Usage

From a task's harbor_task/ folder, with Harbor installed:

harbor run --path . --agent oracle   # reference solution: reward 1
harbor run --path . --agent nop      # untouched workspace: reward 0

License

Revelo builds these tasks in the Terminal-Bench 4.0 format. License all 5,000+ as is, or have us extend them with new domains or harder tasks. Request the full set.

These samples are for evaluation by your organization only. Please do not use them to train models, and please do not share them outside your organization. The canary string in each file marks this content as benchmark data that must stay out of training corpora.

Contact

data@revelo.com

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