# Piper (text to speech) 1.8.0 (piper-tts): our test log

Canonical: https://theagenticweekly.com/tests/piper · Last verified: 2026-10-25 · Published: 2026-10-25 · Author: Agentic Weekly (operated independently from Texas, US) · Evidence: Tested by us on 2026-10-25. Local open-weight model, not the vendor's hosted models. A smoke test on a CPU-only box, not a benchmark.

> Piper 1.8.0 synthesised 10 sentences (about 41 s of 22.05 kHz audio) on CPU in 1.4 to 1.5 s each including process start; 3.5 s uv install, 167 MB.

## Result at a glance

Table: Piper (text to speech) test record

| Field | Value |
|---|---|
| Result | Passed |
| Version tested | 1.8.0 (piper-tts) |
| Date and time | 2026-10-25, 22:53 CDT (America/Chicago) |
| Task | Install piper-tts with uv, download the en_US-lessac-medium voice, and synthesise ten short sentences to WAV files, one process per sentence. Pass means ten playable WAV files; we also transcribed them back with faster-whisper (see that test). |
| Model used | none (no language model involved) |
| Hardware | Linux x86_64 virtual machine (Debian 13), 8 vCPU (Intel Xeon, 1 thread per core), 15 GiB RAM, no GPU |
| Install (uv) | 3.5 s, 167 MB |
| Per-sentence synthesis (incl. start) | 1.38 to 1.52 s |
| Total audio | 41.3 s |

## What we found

- All 10 sentences synthesised with exit code 0; synthesis took 1.38 to 1.52 s per sentence, of which most is process and model start, so a long-running process would be faster per sentence (not measured).
- Sample rate was 22,050 Hz for this medium-quality voice.
- Round trip: the audio was clear enough that faster-whisper recovered it with a 2.4 percent word error rate in the best configuration (see the faster-whisper test).

## What we ran, step by step

Table: Commands run, wall-clock time and exit code

| Step | Wall time | Exit code | Notes |
|---|---|---|---|
| Install with uv | 3.5 s | 0 | piper-tts 1.8.0 with onnxruntime 1.31.0; 167 MB. Load 6.03. |
| Download voice | 1.45 s | 0 | About 60 MB of voice files; this step needs the network once. |
| Synthesise ten sentences | n/a | 0 | Per sentence 1.38 to 1.52 s including interpreter start; audio 3.32 to 5.21 s each, 41.28 s in total. |

Exact commands (paths shortened)

```
# Install with uv
uv venv -p 3.13 work/py/piper && VIRTUAL_ENV=work/py/piper uv pip install --no-cache -q piper-tts

# Download voice
python -m piper.download_voices en_US-lessac-medium

# Synthesise ten sentences
python -m piper -m en_US-lessac-medium -f s<N>.wav -- "<sentence>"
```

## Raw output (excerpts)

Per-sentence record (first four)

```
0: 1.52 s for 5.12 s of audio: The agentic weekly newsletter covers new releases from open source projects every week.
1: 1.46 s for 3.32 s of audio: Please add seventeen and twenty five, and tell me the result.
2: 1.47 s for 3.68 s of audio: Local language models can run on a processor without a graphics card.
3: 1.45 s for 5.21 s of audio: The model context protocol lets an assistant call tools over standard input and output.
```

## Gotchas and things that broke

- The Python package is GPL-3.0 licensed (OHF-Voice/piper1-gpl); check that licence before embedding it in a product.
- Voices are separate downloads; the package alone cannot speak.

## What we did not test

- Voice quality as judged by a person (we only measured machine round-trip accuracy), other voices and languages, streaming, and GPU use.
- One voice only; a smoke test.

## Reproduce it

Versions change. These commands install whatever is latest on the day you run them unless a version is pinned, so expect different results later. The version we measured is in the table above.

```
uv venv -p 3.13 .venv && VIRTUAL_ENV=.venv uv pip install piper-tts
.venv/bin/python -m piper.download_voices en_US-lessac-medium
.venv/bin/python -m piper -m en_US-lessac-medium -f out.wav -- "Hello from Piper."
```

## How to read this test

Every number on this page was measured on this one machine, which also ran other jobs, so timings are indicative and vary run to run. A pass means our small task worked once or as stated, a fail means it did not work as we ran it; neither says how the tool behaves with a vendor's frontier model, on a GPU, or at scale. Where a tool could not run without an account or a GPU, we say so instead of guessing.

See the [testing rig](https://theagenticweekly.com/methodology#testing-rig) for the hardware, the local model and the rules we follow, and the [test hub](https://theagenticweekly.com/tests) for every other test.

## FAQ

### Does Piper run without a GPU?

Yes: 10 sentences took 1.4 to 1.5 s each on 8 CPU cores with no GPU.

## Sources

- [Piper repository (GPL fork)](https://github.com/OHF-Voice/piper1-gpl) (fetched 2026-10-25)

## Related

- [All test logs](https://theagenticweekly.com/tests)
- [Methodology and testing rig](https://theagenticweekly.com/methodology#testing-rig)
- [Study: a voice round trip with Piper and faster-whisper](https://theagenticweekly.com/research/voice-round-trip-piper-faster-whisper)

## How to cite

Agentic Weekly, "Piper (text to speech) 1.8.0 (piper-tts): our test log", last updated 2026-10-25, https://theagenticweekly.com/tests/piper