# FIT-GGUF 为 MiniCPM5-2B 带来可控尺寸混合精度量化

- 来源：OpenBMB (@OpenBMB)
- 发布时间：2026-09-24 21:00
- AIHOT 分数：46
- AIHOT 链接：https://aihot.news/items/cmufjrbz104nxro6oes9vef87
- 原文链接：https://x.com/OpenBMB/status/2103107192068993094

## AI 摘要

FIT-GGUF 为 MiniCPM5-2B 提供可控尺寸的混合精度量化，用户可设定目标文件大小或保真度档位，由工具自动分配各张量精度并预测、生成、验证最终 GGUF。

## 正文

🚀 FIT-GGUF brings controllable-size mixed-precision quantization to MiniCPM5-2B
Developer @Scorp1o_117 used FIT-GGUF to build MiniCPM5-2B GGUF variants around specific size and quality targets.
Instead of choosing a fixed quantization preset, you can set a target file size or fidelity tier, and FIT-GGUF automatically decides how much precision to allocate to different tensors—then predicts, generates, and verifies the final GGUF.

✨ What’s included
🧠 Tensor-level mixed-precision quantization
📦 Four MiniCPM5-2B builds from ~1.14 GiB to ~1.46 GiB
🎯 Quality / Balanced / Compact / Mini presets
📊 KL Divergence and Same-top evaluation
✅ Generated file sizes matched the predicted targets

A nice example of how MiniCPM5-2B can be tuned for different memory and deployment constraints, without being locked into a single Q4/Q5-style quantization preset.

Check out FIT-GGUF and try building a MiniCPM5-2B variant that fits your own device budget.

🤗Model: http://huggingface.co/SC117/MiniCPM5-2B-abliterated-FIT-GGUF/tree/main
http://huggingface.co/openbmb/MiniCPM5-2B