I created the Smoke24 subset because I needed a relatively quick benchmark that could run locally on an RTX 3090-class machine in a couple of hours. The goal is to get a practical read on model performance and stability under a real agentic Terminal-Bench workload, without paying the turnaround cost of a much larger benchmark every time a quantization, context, or serving setup changes.

Smoke24 is therefore a fast local signal, not a replacement for the full Terminal-Bench 2.0 leaderboard.

Canonical publication surfaces:

HF Dataset: https://huggingface.co/datasets/XReyRobert/smoke24-agentic-benchmarks
Interactive HF Space: https://huggingface.co/spaces/XReyRobert/gptq-pro-smoke24-agentic-3090

This repository separates three concerns:

data/public: aggregate benchmark data intended for public distribution.
reports/public: human-readable reports and static images generated from public aggregate data.
site: generated static dashboard output, suitable for a Hugging Face static Space or static web host.

Raw Terminal-Bench run directories, model transcripts, private endpoint details, and IBM Bob/internal comparison artifacts are intentionally not versioned here.

Quick Start

python3 -m venv .venv
. .venv/bin/activate
pip install -r requirements.txt
make validate
make build
make serve

Then open http://127.0.0.1:8765.

Current Dataset

Benchmark: Terminal-Bench 2.0 Smoke24
Agent: Terminus-2
Local hardware lens: RTX 3090-class serving boundary
Public dashboard data: data/public/derived
External public references: data/public/external

External public rows are success-rate references only. They are not placed on local wall-time or local serving-cost axes.

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