Jev case: Built an alternative version of @typesafeai but
Rebuilt a TypeSafe-style decision pipeline on Cerebras with Qwen 3.8 27b, finding TypeSafe cheaper and faster.
The original post
Built an alternative version of @typesafeai but on @cerebras with Qwen 3.8 27b.
Similar quality, similar performance, but vastly different cost. TypeSafe was way cheaper, and did beat Qwen on performance.
Closest we can get using LLMs I think.
Source:
Quoted post
@CompleteSkeptic34.6M viewssourceAfter co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster • 40-400x
What the author linked
- github.com/iammrduncan/ty…
- GitHub - iammrduncan/typesafe-ai-benchmark: This is a LLM Gateway that mimics typesafe ai structured output. Like an imposter Jev. — This is a LLM Gateway that mimics typesafe ai structured output. Like an imposter Jev. - iammrduncan/typesafe-ai-benchmark
Engagement when collected
Numbers are a snapshot taken from X when the case was added to the library (schema v1, collected 2026-09-19); they will not match today.
Where this case fits
Filed under general Jev builds. In the pattern Jev is built for, the model answers a bounded question per step — and ordinary code acts on the answer, because the answer is already a value rather than a paragraph. Browse the full case library for the work it sits next to.
Related Jev cases
Keep browsing: all 1173 Jev cases · more from @iamMrDuncan · builders · what Jev is
Last updated: 2026-09-22 · sources & corrections · every card links to its author's original post