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Frameworks & Starter Kits

microgpt in MLPL

Last updated 2026-09-23 · benchmark measured 2026-09-23 — deterministic & reproducible

Side-by-side comparison of a GPT name-generator implemented in Python, Rust, and MLPL.

50/100
7/7 frames
Top 97% of 14,138 measured
Legit Benchmark — the simple average of 7 measured frames. Frames we could not measure are left out of the average, never counted as zero. Every frame is shown below with its evidence.
Checked 2026-09-23 · scores move as sites change

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Legit.Show scored microgpt in MLPL 50/100 on 2026-09-23, measured across all 7 frames from its public surface. legit.show/s/softwarewrighter-github-io/2026-09-23

Is microgpt in MLPL production-ready?

Legit.Show scores microgpt in MLPL 50 out of 100 — the simple average of its 7 measured frames. Legit.Show ran its deterministic 7-Frame production-readiness benchmark on microgpt in MLPL (public-surface assessment), measured from the public surface with no LLM in the scoring path. Its strongest frame is Performance; its weakest is Discoverability. Every frame it averages is published with its evidence on the Legit.Show listing.

The 7 Frames

What we measured

Who it's for

Machine learning educators · Language designers · Array language enthusiasts · Algorithm implementers · Performance researchers

Sources and updates

Description
Taken from softwarewrighter.github.io's own website on 2026-09-23.
Benchmark
Measured by Legit.Show from the live site, the way any visitor sees it — with no access to its code or accounts. Same method for every product, and no AI decides the score. Last checked 2026-09-23.

Put together from public information, without microgpt in MLPL's involvement. If anything here is wrong, tell us and a person will check it.

Visit microgpt in MLPL → · Alternatives to microgpt in MLPL → · How this was measured →

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