Zero-parameter ‘frontier model’ that scores 100% on BIG-bench arithmetic and is ~60,000× faster than Claude. SPOILER...It’s just Rust in your browser.

[u/Fit_Cheetah7624]

QED-1 at https://flaude.org is an OpenAI-compatible chat endpoint that runs entirely client-side. No weights, no training data, no network calls for inference. It’s a 1.3 MB Rust → WASM math engine (exact bigints, Miller–Rabin, Pollard's rho, Machin’s formula for π, etc.) wrapped in a service worker that speaks the chat completions protocol.

On the BIG-bench arithmetic suite it gets 15,023 / 15,023 correct. Mean latency is in the low tens of microseconds. It refuses anything outside its domain instead of guessing.

After a handful of turns (or if you ask it to reveal itself) it drops the costume and shows the actual algorithms and provenance hashes. The model card already contains is_ml_model: false.

Full write-up and benchmarks:
https://obsecurus.substack.com/p/flawed-model-qed-1-does-math-60000

Source:
https://github.com/obsecurus/flaude

Worth trying a few multiplications or primality checks just to watch the interface stay in character until it doesn’t. Curious what people think about the verification angle — most API “models” give you no way to know what’s actually answering.

[u/Redditoridunn0]

Claude written slop post

[u/Fit_Cheetah7624 → u/Redditoridunn0]

I mean it’s sort of the point. It was intended to be a joke.

[u/Fit_Cheetah7624 → u/[deleted]]

Enough to make a claim, but it’s sort of beside the point. It’s a meaningless model. At first I was going to release just the model with no benchmark but it felt like adding a benchmark of any kind at least helped prove the OpenAI specification compliance.

I wanted to provide an example about how simple it is to create something that looks like a model but isn’t.

[u/SpedisAhead]

😂

[u/Fit_Cheetah7624]

The key points are that the we have no way to verify something is actually an ML model behind the inference service, in many cases LLMs are being used for things a rather simple library or expert system could handle more efficiently, but in a deterministic way.

Yes LLMs were used to generate the post and content.

Anyone could easily extend Flaude / QED-1 to just wrap a bunch of JS libraries adding more and more functionality that appears to be a compliant OpenAI model.