Skip to main content
turbobench

⚖️ Matched environments. Measured fairly. ⚖️

turbobench is a local Python CLI for reinforcement-learning environment authors, researchers, and provider maintainers who need fair performance comparisons between compatible implementations and standardized cross-provider parity checks. Immutable parity profiles pin the original authority, exact checks, full workload, and quick development workload. Both parity and benchmark runs produce portable, self-verifying evidence.

Optional comparison videos replay the same locked providers and semantic action trajectory. Only valid, conclusive evidence can produce unmarked promotional media; diagnostic output is clearly watermarked.

Install

Install turbobench-cli 2.0.0 from PyPI:

uv tool install turbobench-cli==2.0.0

Alternatively, install it in an active virtual environment with python -m pip install turbobench-cli==2.0.0. The installed command and Python import remain turbobench.

For a development checkout:

git clone https://github.com/tsilva/turbobench.git
cd turbobench
uv sync --frozen --group dev

Run turbobench profiles list and turbobench providers list to choose a compatible profile and provider pair. Prefix CLI commands with uv run when working from a development checkout.

Commands

turbobench doctor vizdoom/basic-v1       # check the host, tools, and profile assets
turbobench profiles list                 # list immutable workloads
turbobench providers list                # list built-in and registered providers

turbobench parity supermario/canonical-v2 \
  --candidate env-supermariobrosnes-turbo-emu@checkout:/absolute/path/to/repo \
  --allow-dirty --quick                         # test current work diagnostically

turbobench parity vizdoom/basic-v2 \
  --candidate env-vizdoom-turbo@artifact:/absolute/path/to/final.whl \
  --output turbobench-parity/vizdoom            # certify the exact final wheel

turbobench verify-parity turbobench-parity/vizdoom --require-canonical

turbobench compare vizdoom/basic-v1 \
  --left env-vizdoom-turbo@1.3.0.post27 \
  --right vizdoom@1.3.0 \
  --output turbobench-results/vizdoom            # create a result bundle

turbobench compare breakout/start-v3 \
  --left env-breakoutatari2600-turbo-native@VERSION \
  --right stable-retro@1.0.1 \
  --output turbobench-results/breakout-vs-stable-retro

turbobench compare breakout/start-v3 \
  --left env-breakoutatari2600-turbo-native@VERSION \
  --right env-stableretro-turbo@VERSION \
  --output turbobench-results/breakout-vs-stable-retro-turbo

turbobench verify turbobench-results/vizdoom  # verify integrity and consistency
turbobench report turbobench-results/vizdoom  # print the generated report
turbobench promo turbobench-results/vizdoom --diagnostic

uv run --frozen ruff check .                    # lint the project
uv run --frozen pytest -m "not acceptance"      # run tests without proprietary assets

Long-running commands write progress to standard error and reserve standard output for their final machine-readable JSON.

Notes

  • The controller supports Python 3.11 and newer. Provider runtimes default to CPython 3.14. uv, FFmpeg, and FFprobe are required.
  • Current performance profiles cover supermario/canonical-v1, breakout/start-v3, and vizdoom/basic-v1. Historical profiles remain available for verifying their existing result bundles. Shapes 1, 16, and 32 are measured and reported independently.
  • Provider references accept provider, provider@latest, provider@VERSION, provider@artifact:/absolute/path.whl, and provider@checkout:/absolute/path. latest excludes prereleases, yanked releases, incompatible artifacts, and releases still inside the seven-day quarantine.
  • Set TURBOBENCH_ROM_PATH, TURBOBENCH_ASSET_ROOT, or RETRO_DATA_PATH to locate required local game payloads. ROMs and local paths are never written to portable bundles; only canonical digests are recorded.
  • The breakout/start-v3 profile compares the Atari 2600 Breakout Start workload against either original Stable Retro or Stable Retro Turbo. Replace VERSION with an exact release, use @latest, or select a clean checkout with @checkout:/absolute/path.
  • Every official result must pass provider compatibility, matched correctness, system-load, alternating paired-measurement, statistical uncertainty, provenance, and asset gates. Quick runs and explicit overrides remain diagnostic.
  • Exact release parity accepts only the final local wheel on the chosen canonical host. Checkout snapshots include tracked edits and nonignored untracked source, so developers do not need to commit before running a quick diagnostic check.
  • Turbo providers are preflighted against the normative Turbo Vector API v2 contract. Contract reports are hash-bound into result bundles; malformed v2 providers stop before any workload, while historical v1 providers remain diagnostic-only.
  • Result bundles contain the exact provider lock, shape-local statistics, report, chart, raw evidence, verification records, and optional media. manifest.json binds every portable file by size and SHA-256; turbobench does not upload or publish bundles.
  • Official v1 hosts are Apple-silicon macOS and x86-64 Linux. Third-party providers can register through the turbobench.providers entry-point group.

Architecture

turbobench architecture

License

MIT

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

turbobench_cli-2.0.5.tar.gz (2.1 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

turbobench_cli-2.0.5-py3-none-any.whl (93.8 kB view details)

Uploaded Python 3

File details

Details for the file turbobench_cli-2.0.5.tar.gz.

File metadata

  • Download URL: turbobench_cli-2.0.5.tar.gz
  • Upload date:
  • Size: 2.1 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/7.0.0 CPython/3.13.14

File hashes

Hashes for turbobench_cli-2.0.5.tar.gz
Algorithm Hash digest
SHA256 d436a2de422c7a062fa8962888bb325fd2cb2ad8d994dd005036f487f8ee5995
MD5 7dd7eef5dc51c0d7a13886ee201e9646
BLAKE2b-256 0643d5050e17c3e57701cc4a5f059587d9c1aa5a29c5ba60cd141c5e107cf6e4

See more details on using hashes here.

Provenance

The following attestation bundles were made for turbobench_cli-2.0.5.tar.gz:

Publisher: release.yml on tsilva/turbobench

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file turbobench_cli-2.0.5-py3-none-any.whl.

File metadata

  • Download URL: turbobench_cli-2.0.5-py3-none-any.whl
  • Upload date:
  • Size: 93.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/7.0.0 CPython/3.13.14

File hashes

Hashes for turbobench_cli-2.0.5-py3-none-any.whl
Algorithm Hash digest
SHA256 6055db4d79d6d58093da71e344dba2322b641dbfe945c1bbc76b9c063607f580
MD5 138a37b933c4c8aca2010762b74cc1e1
BLAKE2b-256 c4ada76c3160f011220a6414ef50f50467ac60676fa6c21d3d361d74f8d6ac0a

See more details on using hashes here.

Provenance

The following attestation bundles were made for turbobench_cli-2.0.5-py3-none-any.whl:

Publisher: release.yml on tsilva/turbobench

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Release history Release notifications | RSS feed

2.0.7

2 files

2.0.6

2 files

This release

2.0.5 This release

2 files

2.0.4

2 files

2.0.3

2 files

2.0.1

2 files

1.0.5

2 files

1.0.2

2 files

1.0.1

2 files

1.0.0

2 files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page