# genpark-ternary-weight-1bit-quantized-gemm-kernel-skill

> genpark-ternary-weight-1bit-quantized-gemm-kernel-skill — alphaparkinc-genpark-ternary-weight-1bit-quantized-gemm-kernel-skill. Use this tool when you need to optimize matrix multiplication for high-efficiency inference, particularly with 1.58-bit ternary weights. It solves problems related to efficient neural network inference, such as reducing computational resources and improving performance. The tool takes in quantized weights and matrix inputs, producing optimized output for low-latency applications.

Canonical page: https://skillsregistry.net/skills/alphaparkinc-genpark-ternary-weight-1bit-quantized-gemm-kernel-skill  
JSON: https://api.skillsregistry.net/v1/skills/alphaparkinc-genpark-ternary-weight-1bit-quantized-gemm-kernel-skill

## Description

1.58-bit ternary weight GEMM kernel for high efficiency inference (BitNet style)

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/alphaparkinc/genpark-ternary-weight-1bit-quantized-gemm-kernel-skill)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "alphaparkinc-genpark-ternary-weight-1bit-quantized-gemm-kernel-skill"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/alphaparkinc-genpark-ternary-weight-1bit-quantized-gemm-kernel-skill` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/alphaparkinc-genpark-ternary-weight-1bit-quantized-gemm-kernel-skill/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt