Yes. twinny runs. Argusic installed and launched it on a clean machine in 4 minutes, hitting 0 errors on the way, and recorded the session.

How did Argusic test twinny?

On a fresh, disposable machine, with every command recorded and the repository pinned at commit 4685b7fb87ca. One attempt is recorded, and the full method is on the methodology page.

What did it cost to test twinny?

The run that produced this verdict cost $0.03: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.

How long does twinny take to install?

4.2 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 twinny need a GPU?

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

What goes wrong when installing twinny?

Nothing did, in the recorded run: zero errors between clone and running.

Where is the evidence for twinny?

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.

twinny

Open-source AI coding assistant for VS Code. Code completion, chat, edits and reviews with local or hosted models. Your models, your infrastructure.

Runssource: GitHub homepageTypeScriptMITcommit 4685b7fb87ca

TypeScript, MIT licensed. The project labels itself: ai coding assistant, artificial intelligence, code chat, code completion, code generation, code review, code review assistant and developer tools.

twinny runs. An Argusic agent installed it in 4.2 minutes and hit no errors on a clean machine with no GPU, and the whole session was recorded.

npm install adds 1549 packages, build and tsc compile succeed, the Mocha test suite passes 642 tests in the VS Code extension host, the twinny-node CLI displays help and usage, the twinny-server CLI initializes config files and serves an HTTP gateway on a real port, and all commands handle missing dependencies gracefully with descriptive error messages.
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: $0.03 (measured)
recorded runs: 1
last tested: 2026-09-23
stars: 3,650
forks: 230
open issues: 48
watchers: 1
size: 67 MB
created: 2023-08-21
last push: 2026-09-22

Subject data from GitHub, linked at the top of this page, refreshed 2026-09-23. 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.

Install time: 4 minutes
Cold machine to finish: 6 minutes
Errors hit and fixed: 0 hit, 0 fixed with no human help
How the result was proved: npm test exited 0, 642 passing, 4 pending
Model tokens used: 57,299
Exact commit tested: 4685b7fb87ca
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.

  data:     /home/runner/.twinny/server (format 1)
  usage:    /home/runner/.twinny/server/usage (kept 30 days)
  recording: off · jsonl at /home/runner/.twinny/server/recordings/jsonl, kept 90 days
2026-09-23T07:21:36.427Z info event=gateway.started keys=0 host=127.0.0.1 port=8765 protocol=twinny…
  backend:  local-ollama is not answering (provider-unavailable); its aliases will fail until it is.
2026-09-23T07:21:36.459Z info event=backend.probe kind=provider-unavailable ms=31 provider=local-ol…
2026-09-23T07:21:41.021Z info event=gateway.stopping active=0 signal=SIGTERM grace=5000
2026-09-23T07:21:41.073Z info event=gateway.stopped
All systems verified. Here's the final report:
tokens used
57,299
All systems verified. Here's the final report:

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 4.2 minutes, faster than the median of the 4 comparable projects Argusic has measured.
Nothing broke on the way: zero errors between clone and running.
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 5 ai-coding-assistant projects Argusic has installed and timed, twinny was the 3rd fastest to reach a running state, and 5 of 5 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 4.2 minutes after the clone.
Following its own README: the documented path worked with nothing to fix.

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	0.03	2026-09-23 07:22 UTC

Topics (from GitHub)

ai-coding-assistant artificial-intelligence code-chat code-completion code-generation code-review code-review-assistant developer-tools embeddings llamacpp llm local-ai ollama private-ai self-hosted self-hosted-ai self-hosted-llm vscode-extension

Embed the badge

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

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

Questions

Does twinny run?: Yes. twinny runs. Argusic installed and launched it on a clean machine in 4 minutes, hitting 0 errors on the way, and recorded the session.
How did Argusic test twinny?: On a fresh, disposable machine, with every command recorded and the repository pinned at commit 4685b7fb87ca. One attempt is recorded, and the full method is on the methodology page.
What did it cost to test twinny?: The run that produced this verdict cost $0.03: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
How long does twinny take to install?: 4.2 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 twinny need a GPU?: Not to start. Argusic reached a running state on a machine with no GPU.
What goes wrong when installing twinny?: Nothing did, in the recorded run: zero errors between clone and running.
How does twinny compare with the alternatives?: Of the 5 ai-coding-assistant projects Argusic has installed and timed, twinny was the 3rd fastest to reach a running state, and 5 of 5 reached one at all.
Where is the evidence for twinny?: 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.