# genpark-int8-symmetric-per-tensor-quantizer-skill

> genpark-int8-symmetric-per-tensor-quantizer-skill — alpha-park-genpark-int8-symmetric-per-tensor-quantizer-skill. Use this tool when you need to optimize large language models (LLMs) by reducing their memory footprint and improving computational efficiency. It provides symmetric INT8 per-tensor and per-channel quantization for LLM weights and activations, solving problems related to model size and inference speed. The tool takes in LLM models and outputs quantized models with telemetry data on signal-to-noise ratio (SNR) and mean squared error (MSE) reconstruction.

Canonical page: https://skillsregistry.net/skills/alpha-park-genpark-int8-symmetric-per-tensor-quantizer-skill  
JSON: https://api.skillsregistry.net/v1/skills/alpha-park-genpark-int8-symmetric-per-tensor-quantizer-skill

## Description

Symmetric INT8 per-tensor and per-channel quantization engine for LLM weights and activations, with SNR and MSE reconstruction telemetry.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

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

## Source

- **Source listing:** [GitHub](https://github.com/Alpha-Park/genpark-int8-symmetric-per-tensor-quantizer-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": "alpha-park-genpark-int8-symmetric-per-tensor-quantizer-skill"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/alpha-park-genpark-int8-symmetric-per-tensor-quantizer-skill` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/alpha-park-genpark-int8-symmetric-per-tensor-quantizer-skill/pull`

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