Qwen 3.6 27B quantization tests ask how far 2-bit compression can go

pmigdal · reddit · 2026-07-27

This blog post examines whether different quantizations of Qwen 3.6 27B preserve model quality, using the “pelican” comparison as the headline example.

• The article compares full precision BF16 against a 2-bit quantization variant labeled UD-IQ2XXS.
• The core question is whether aggressive compression breaks quality enough to matter in practice.
• The image suggests a dramatic size reduction from 54.7 GB to 9.6 GB, framing the trade-off between memory use and output quality.
• Overall, the post is about evaluating how far quantization can go before the model starts degrading in noticeable ways.

Original post →

More from Models

• French prize-winning novel suspected of AI: $1,000 challenge over detector results — Afinetheorem · 2026-09-23
• Third-party test: Claude Opus 5.5 renders finer 3D scenes but costs 13x more than GPT-6 Sol — testingcatalog · 2026-09-23
• GPT-6 Sol priced at half of Opus 5.5 as Sol and Luna go 'dirt cheap' — ZeroStateReflex · 2026-09-23
• Tester claims Claude Opus 5.5 has the best visual design output of any model tested — burny_tech · 2026-09-23
• Meta's Alexandr Wang reveals muse has been in the works since at least Sept 2025 — adrianscottcom · 2026-09-23
• GPT-6 Sol Codex system prompt leaked: over 294,000 characters dumped on GitHub — gaganghotra_ · 2026-09-23

Models channel →