🧠
zinc model by zolotukhin
⭐ 46.5
🧠
Model

zinc

by zolotukhin zolotukhin/zinc
Free2AITools Nexus Index
46.5
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 56
P: Popularity 60
R: Recency 89
Q: Quality 70
Tech Context
Vital Performance —
Source β†’

Task categories from upstream metadata

πŸ’¬Chat & Dialogue

Technical Constraints

Experimental / High Latency
Low FNI signal 46.5 FNI Score
Tiny - Params
- Context
0 Downloads
Commercial MIT License
Model Information Summary
Entity Passport
Registry ID zolotukhin/zinc
License MIT
Provider github
πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{zolotukhin_zinc,
  author = {zolotukhin},
  title = {zinc Model},
  year = {2026},
  howpublished = {\url{https://github.com/zolotukhin/zinc}},
  note = {Accessed via Free2AITools.}
}
APA Style
zolotukhin. (2026). zinc [Model]. Free2AITools. https://github.com/zolotukhin/zinc

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ™ Git Clone
git clone https://github.com/zolotukhin/zinc

βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 56
Popularity (P) 60
Recency (R) 89
Quality (Q) 70

πŸ’¬ Index Insight

FNI V2.0 for zinc: Authority (A:56), Popularity (P:60), Recency (R:89), Quality (Q:70). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

Data Sources / Provenance

HuggingFace API GitHub Metadata Arxiv Citation DB Methodology
Open data Updated: Live data
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πŸš€ What's Next?

πŸ“Š

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⚑

Deployment reference

Understand deployment options

Technical Deep Dive

ZINC Logo

ZINC β€” Zig INferenCe Engine

CI Status Zig Version License Platform Website ZINC Discord

Local LLM inference on AMD GPUs and Apple Silicon β€” no ROCm, no MLX, one binary.

ZINC Chat Demo β€” streaming inference on AMD RDNA4
35B parameter model running locally β€” Zig + Vulkan/Metal, no ROCm, no MLX

Supported Platforms

Platform GPU Backend Status
Linux AMD RDNA4 (RX 9070, AI PRO R9700) Vulkan Primary β€” hand-tuned shaders
Linux AMD RDNA3 (RX 7900 XTX, etc.) Vulkan Supported
macOS Apple Silicon (M1, M2, M3, M4, M5) Metal Supported β€” native MSL shaders

Start Here

Works the same on Linux (AMD GPU) and macOS (Apple Silicon):

bash 
git clone https://github.com/zolotukhin/zinc.git
cd zinc
zig build -Doptimize=ReleaseFast

# On RDNA4 Linux, enable cooperative matrix
export RADV_PERFTEST=coop_matrix  # skip on macOS

# Verify GPU, shaders, and runtime
./zig-out/bin/zinc --check

# See which models fit this machine
./zig-ou

⚠️ Incomplete Data

Some information about this model is not available. Use with Caution - Verify details from the original source before relying on this data.

View Original Source β†’

πŸ“ Limitations & Considerations

  • β€’ Benchmark scores may vary based on evaluation methodology and hardware configuration.
  • β€’ VRAM requirements are estimates; actual usage depends on quantization and batch size.
  • β€’ FNI scores are relative rankings and may change as new models are added.
  • ⚠ License Unknown: Verify licensing terms before commercial use.

Social Proof

GitHub Repository
290Stars
14Forks
Repo Issues
πŸ™ Data Source: GitHub β†—
πŸ”„ Updated daily

Source summary: Based on GitHub metadata. Not a recommendation.

πŸ“Š FNI Methodology πŸ“š Knowledge Baseℹ️ Verify with original source

πŸ›‘οΈ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

πŸ†” Identity & Source

id
gh-model--zolotukhin--zinc
slug
zolotukhin--zinc
source
github
author
zolotukhin
license
MIT
tags
amd, amdgpu, gpt, gpu, openai, pytorch, qwen3, rdna3, rdna4, transformer, zig

βš™οΈ Technical Specs

architecture
null
params billions
null
context length
null
pipeline tag
text-generation

πŸ“Š Engagement & Metrics

downloads
0
stars
290
forks
14

Data indexed from public sources. Updated daily.