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eikos

Open, calibrated, single-pass typed-decision models (4B & 27B) for finance and trading

Details

External ID
1384337258
Source
GITHUB
Company
—
Product
eikos
Website domain
huggingface.co
Launched
Sept. 23, 2026
Cohort
—
Upvotes
25
Upvotes percentile
0.6742890084550346
Tags
calibration, decision-making, finance, llm, mlx, trading, vllm
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
Fintech
Function
Model & infra
Audience
Developer
AI stance
AI-native
Project type
Hobby / open-source project
Normalized one-liner
open decision models for finance and trading
Manually corrected
False

Could you build this?

No Training and calibrating 4B and 27B parameter models for financial trading requires proprietary quantitative datasets, substantial GPU compute clusters, and specialized quantitative finance expertise.

What it would actually take: Requires pre-training/fine-tuning large LLMs (4B to 27B parameters) using PyTorch, Megatron-LM/DeepSpeed, on clusters of H100s with vast collections of curated historical financial market data, SEC filings, and order book states. Hard parts include reward modeling, probability calibration for financial edge cases, and high-frequency backtesting validation.

Competitors

Other products that read as similar to this one — 1001 launches clear the similarity bar, closest 8 shown.

Attention rank: #300 of 1002 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 329 days after the earliest competitor.

Other launches for this product