Yes. openwhispr runs. Argusic installed and launched it on a clean machine in 2 minutes, hitting 5 errors on the way, and recorded the session.

How did Argusic test openwhispr?

On a fresh, disposable machine, with every command recorded and the repository pinned at commit 9d9980ae9042. One attempt is recorded, and the full method is on the methodology page.

What did it cost to test openwhispr?

The run that produced this verdict cost $0.59: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.

How long does openwhispr take to install?

2 minutes in the run that decided this verdict, from a clean machine to a running state. That is one measured attempt, not an average.

Does openwhispr need a GPU?

Not to start. Argusic reached a running state on a machine with no GPU.

What goes wrong when installing openwhispr?

5 things broke in the recorded run, and 5 were fixed without human help. Each one, and the time it cost, is listed on this page.

Where is the evidence for openwhispr?

The recorded run is on this page, each linking to its full log and terminal recording, stored with a sha256 fingerprint so it cannot be quietly altered.

openwhispr

Voice-to-text dictation app with local (Nvidia Parakeet/Whisper) and cloud models (BYOK). Privacy-first and available cross-platform.

Runssource: GitHub homepageJavaScriptMITcommit 9d9980ae9042

JavaScript, MIT licensed. The project labels itself: ai, anthropic, cross platform, gemini, groq, linux, macos and nvidia.

openwhispr runs. An Argusic agent installed it in 2 minutes and hit 5 errors and fixed every one without help on a clean machine with no GPU, and the whole session was recorded.

npm install succeeds, all 944 tests pass with Node 24 and the custom loader bootstraps, test script runs all test suites without failures.
What the agent ended up with on a clean machine, in its own words. How this is measured

Measured by Argusic on a fresh machine every time. Every number links to its evidence. Argusic Score 100 of 100 (the mean of this project's run scores).

At a glance

verdict: Runs
Argusic Score: 100 / 100
cost of the verifying run: $0.59 (measured)
recorded runs: 1
last tested: 2026-09-28
stars: 8,710
forks: 1,070
open issues: 379
watchers: 19
size: 122 MB
created: 2025-06-19
last push: 2026-09-28

Subject data from GitHub, linked at the top of this page, refreshed 2026-09-28. Test data by Argusic (CC BY 4.0); every number links to a run page with the full log, the recording, and their sha256 hashes.

What was measured

From the run that decided this verdict. Every line is a recorded value, not an estimate.

Time lost to each failure while testing openwhispr, drawn from the recorded run — Every bar is a failure the agent recorded, with the time it cost. Drawn from this run, not from anywhere else.

What went wrong, in the agent's own words

The agent's own words, worst first, never rewritten into advice.

tsx wraps ESM imports in {default: ...} for CJS test files, breaking destructuring in await import('.ts')20 minutes
Node.js v18 installed but project requires >=242 minutes
Node --experimental-strip-types does not resolve extensionless relative imports (import './logger' instead of './logger.ts')
JSON imports need import attributes and named exports don't work natively
require('.tsx') for JSX components fails with strip-types

Install time: 2 minutes
Cold machine to finish: 71 minutes
Errors hit and fixed: 5 hit, 5 fixed with no human help
How the result was proved: node --experimental-strip-types --require ./scripts/test-bootstrap.cjs --import ./scripts/register-test-loader.mjs --test gave 944 passed, 0 failed across all 8 test directories
Model tokens used: 531,589
Exact commit tested: 9d9980ae9042
Container image: sha256:cdd920bce783

What was not measured

The other half, so you can see exactly how far this evidence goes. A gap is printed as a gap and never filled in.

Peak GPU memory: this ran on a CPU machine, so there was no GPU to sample
Behaviour over a long run: each attempt uses the smallest documented settings and a fixed time budget, so this measures whether it runs, not how it holds up under load

The end of the recording

The last lines of the terminal session that decided this verdict, exactly as they were recorded.

From my sequential runs I observed **all tests passing**:
| Suite | Tests | Pass | Fail |
|---|---|---|---|
| utils | 176 | 176 | 0 |
| scripts | 4 | 4 (1 skipped) | 0 |
| hooks | 44 | 44 | 0 |
| lib | 151 | 151 | 0 |
| stores | 53 | 53 | 0 |
| helpers | 414 | 414 | 0 |
| services | 47 | 47 | 0 |
| components | 55 | 55 | 0 |
| **Total** | **~944** | **~944** | **0** |

Replay the whole session, every command from a clean machine to this point.

How it was tested

One agent, one container, no human help. It installs the project the way its own documentation says to, runs it, and fixes what breaks. Everything below is recorded as it happened: the terminal session, the log and the exact commit. The full method.

Strengths and limits

Measured facts, not opinions. How this is written.

What went well

Reached a running state on a clean machine, with the session recorded.
Installed in 2 minutes, faster than the median of the 54 comparable projects Argusic has measured.
Recovered from all 5 errors without a human stepping in, which says the failures are documented well enough to solve.
Ran without a GPU, so it does not need one to start.
Licensed MIT, as reported by its host.

What did not, or is not known

Measured once so far. A single attempt shows it can run, not that it runs reliably.

Of the 55 ai projects Argusic has installed and timed, openwhispr was the 10th fastest to reach a running state, and 42 of 55 reached one at all.

What it is a reasonable choice for

Trying it on a laptop or a small server: it reached a running state without a GPU.
A quick evaluation: it was running 2 minutes after the clone.

Also tested, in the same area

Every one of these was installed and run by Argusic on a clean machine. Nothing appears here that was not tested.

Run history

tested by	attempt	outcome	score	cost USD	when
Argusic Runner	1/3	Runs	100.00	0.59	2026-09-28 02:27 UTC

Topics (from GitHub)

ai anthropic cross-platform gemini groq linux macos nvidia open-source openai parakeet speech-to-text transcribe whisper windows

Embed the badge

Markdown for the project README. It links back here; terms on the terms page.

[![Tested by Argusic](https://argusic.com/badge/openwhispr.svg)](https://argusic.com/subject/openwhispr)

Questions

Does openwhispr run?: Yes. openwhispr runs. Argusic installed and launched it on a clean machine in 2 minutes, hitting 5 errors on the way, and recorded the session.
How did Argusic test openwhispr?: On a fresh, disposable machine, with every command recorded and the repository pinned at commit 9d9980ae9042. One attempt is recorded, and the full method is on the methodology page.
What did it cost to test openwhispr?: The run that produced this verdict cost $0.59: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
How long does openwhispr take to install?: 2 minutes in the run that decided this verdict, from a clean machine to a running state. That is one measured attempt, not an average.
Does openwhispr need a GPU?: Not to start. Argusic reached a running state on a machine with no GPU.
What goes wrong when installing openwhispr?: 5 things broke in the recorded run, and 5 were fixed without human help. Each one, and the time it cost, is listed on this page.
How does openwhispr compare with the alternatives?: Of the 55 ai projects Argusic has installed and timed, openwhispr was the 10th fastest to reach a running state, and 42 of 55 reached one at all.
Where is the evidence for openwhispr?: The recorded run is on this page, each linking to its full log and terminal recording, stored with a sha256 fingerprint so it cannot be quietly altered.