Local Inference Showdown: GLM 5.2 vs DeepSeek V4 Flash Quantization
Sentdex · x · 2026-07-03
Sentdex initially planned to choose a local GLM 5.2 quantization version based on speed and intelligence, but ultimately pivoted to DeepSeek V4 Flash, learning valuable local inference lessons along the way. He provides a local inference score comparison from Terminal Bench v2.1 (using FP8 GLM 5.2 baseline from openrouter) to serve as a reference for quantization selection.
Related event: Local Inference Showdown: GLM 5.2 vs DeepSeek V4 Flash Quantization(2 posts)→
More from Research
- AlphaFold Learned From 50 Years of Experiments, First-Principles Biology Still Needs Wet Labs — vishalmisra · 2026-10-26
- Fern's "context is intelligence" thesis: prediction keeps improving out to 10.2M tokens — bneyshabur · 2026-10-26
- Researchers identify "Forking": train loss falls while validation loss turns up — ZimingLiu11 · 2026-10-26
- Google DeepMind pilots world's first double-blind evaluations for frontier models — scychan_brains · 2026-10-26
- Rewriting scaling law study: optimal synthetic data share rises from 10% to 32% with compute — heghbalz · 2026-10-26
- FLASH: GPU-native deformable sim learns cloth folding in minutes on one RTX 5090 — ChongZzZhang · 2026-10-26