jev-benchmarks
Probability-aware evaluation for typed decision models: calibration, selective risk, latency, and reproducible benchmarks.
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GITHUB · launched Sep 17, 2026 · 15 upvotes (top 52%) · 2 views
Niche: ai benchmarking platforms · 145 launches, 4 in the last 7 days ▼ -56% · Explore this niche →
Category and tags
- Horizontal
- Observability & eval
- Developer
- AI-native
- Hobby / open-source project
- benchmarking
- calibration
- evaluation
- machine-learning
- reproducibility
- selective-classification
- +1 more
Visit website ↗ Source listing ↗
More like this: all 145 launches in ai benchmarking platforms →
Could you build this?
Yes Evaluation benchmarks for probability calibration, selective risk, and latency are standard statistical routines easily implemented in Python with NumPy and SciPy.
Competitors
Other products that read as similar to this one : 2816 launches clear the similarity bar, closest 8 shown.
Attention rank: #1417 of 2817 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).
Launched 323 days after the earliest competitor.
- jevbench · github · 2026-09-19 · 101 upvotes · similarity 0.84
- awesome-jev-typesafe · github · 2026-09-18 · 129 upvotes · similarity 0.80
- decider · github · 2026-09-16 · 130 upvotes · similarity 0.77
- ProbabilityBench · github · 2026-10-14 · 9 upvotes · similarity 0.76
- AnyDecisionModel · github · 2026-09-21 · 9 upvotes · similarity 0.76
- MagibuMizan · github · 2026-09-26 · 9 upvotes · similarity 0.76
- awesome-jev-tools · github · 2026-09-19 · 680 upvotes · similarity 0.75
- Bev · github · 2026-09-23 · 13 upvotes · similarity 0.74
The niche, labels, vibe code rating and competitor comparison on this page are analysis by Nicheloom. If you use them, please credit nicheloom.com. How you may use our data.