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nagi

Typed decisions in one forward pass: Smol 421M, Big 4B and Nagi-HUGE 12B. Reproducible four-system benchmark.

Details

External ID
1383329553
Source
GITHUB
Company
—
Product
nagi
Website domain
github.io
Launched
Sept. 23, 2026
Cohort
—
Upvotes
10
Upvotes percentile
0.28183448629259544
Tags
—
Fetched at
Sept. 27, 2026, 5:02 p.m.
Updated at
Sept. 27, 2026, 5:02 p.m.

Enrichment

Theme
decision model runtimes and tools
Vertical
Horizontal
Function
Model & infra
Audience
Developer
AI stance
AI-native
Project type
Hobby / open-source project
Normalized one-liner
compact language models for structured decision-making in a single forward pass
Manually corrected
False

Could you build this?

No Nagi introduces custom trained foundation models (Smol 421M to HUGE 12B) executing typed decisions in a single forward pass alongside reproducible benchmarking pipelines, requiring large-scale model training infrastructure.

What it would actually take: Building this requires significant GPU clusters, custom dataset curation, model architecture design for constrained/typed single-step token outputs, and pretraining/fine-tuning pipelines via PyTorch/Megatron. Specialized ML research and systems engineering teams with substantial compute budgets are required to train 4B to 12B parameter models.

Competitors

Other products that read as similar to this one — 1000 launches clear the similarity bar, closest 8 shown.

Attention rank: #693 of 1001 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 327 days after the earliest competitor.

Other launches for this product

Same idea, different domain

Nobody's really built a model & infra tool for Fintech yet.