Three quantized versions of @AntLingAGI Ling-3.0-flash-Fin are now available: FP8, FP4 and INT4.
If you’re building real-world financial workflows, you can choose the version that best fits your infrastructure, memory and efficiency needs. 🧵
Now available on HuggingFace and ModelScope:
Hugging Face:
🔗https://t.co/sTH08ebbFl
🔗https://t.co/WszCrs6xpD
🔗https://t.co/VxCC47ABv8
ModelScope: 🔗https://t.co/Gg80aOchXd
🔗https://t.co/CGqOnfbvyx
🔗
quantization — Shrinking a model by storing its numbers less precisely — like rounding — so it runs faster and fits on smaller hardware, at a small quality cost.
Why it matters
Lets teams building financial AI workflows pick FP8, FP4, or INT4 precision to fit their memory and latency budget instead of running one fixed-size model.
