{"slug":"openlair-gptq","source_name":"openlair/gptq","name":"Openlair/Gptq","description":"Post-training 4-bit quantization for LLMs with minimal accuracy loss. Use for deploying large models (70B, 405B) on consumer GPUs, when you need 4× memory reduction with <2% perplexity degradation, or for faster inference (3-4× speedup) vs FP16. Integrates with transformers and PEFT for QLoRA fine-tuning.","version":1,"lift":{"pass_rate_delta_pts":21.74,"pass_rate_pct":91.3,"total_cases":23,"passed_cases":21,"tokens_delta_pct":186,"turns_delta_pct":0,"verdict":"mixed","benchmark_model":"gemini-3.6-flash","grading_method":"judged","completed_at":"2026-08-07T19:46:41.380351+00:00"},"skill_score":0.913,"benchmark_models":[{"model":"gemini-3.6-flash","headline":true,"delta_pts":21.74,"with_pass_pct":91.3,"without_pass_pct":69.6,"tokens_delta_pct":186,"turns_delta_pct":0,"total_cases":23,"cases_aggregated":20,"verdict":"mixed","never_hurt":true,"completed_at":"2026-08-07T19:46:41.380351+00:00","run_id":"802571bf-92d1-40a0-8bc5-730e25af4665","version_number":1,"is_latest_version":true,"gate":null}],"trust":{"skill_safety":"passed","safety_status":"clean","intent_verdict":"safe","content_status":"clean","indexable":true},"license":"MIT","install_count":0,"manifest_hash":"9ae035f5e46e01d27b67aef8f2c87da6bfc6f8b60a27f45f865f1de197c8bfdf","raw_url":"https://app.decimal.ai/s/openlair-gptq/SKILL.md","scorecard_url":"https://app.decimal.ai/skills/openlair-gptq"}