DeepSeek 2.52-bit quantization holds up surprisingly well in testing
nomorebuttsplz · reddit · 2026-08-24
User testing found that a heavily quantized 2.52-bit EXL3 version of DeepSeek Flash performs surprisingly well compared to a slower MXFP4 version, showing no struggle in coding tasks and handling 200k+ context lengths. The post asks if any specific tasks are more fragile to quantization.
More from Models
- Zuck announces Meta Muse Spark Open weights: 816B-param image-text model tuned for Mac Studio — bansalg_ · 2026-10-16
- Google launches revamped Gemma docs hub covering fine-tuning, inference and model internals — _philschmid · 2026-10-16
- Nathan Lambert slams Meta's Muse Open License as 'trash' — natolambert · 2026-10-16
- Google launches Gemini 4 Argon to Ultra and Pro subscribers, touting physics and 3D skills — ShikharMurty · 2026-10-16
- Google gives X users early access to test Argon, not just companies — lyraxana · 2026-10-16
- Grok Voice 3.0 Tops Design Arena Speech Leaderboard, Up 7.4 Points — XFreeze · 2026-10-16