Ring-mini-linear-2.0
Ring-mini-linear-2.0 is an open-weights language model from Ant Group, released October 23, 2025. Its makers disclosed about 16B parameters.
In this technical report, we present the Ring-linear model series, specifically including Ring-mini-linear-2.0 and Ring-flash-linear-2.0. Ring-mini-linear-2.0 comprises 16B parameters and 957M activations, while Ring-flash-linear-2.0 contains 104B parameters and 6.1B activations.
Check it against your own PC →
Can you run Ring-mini-linear-2.0 locally?
Even with 32 GB of VRAM and 32 GB of RAM it is too large to run at a usable speed on a single consumer GPU. Estimates assume 32 GB of DDR5 RAM, a 16K context and llama.cpp-style GGUF quantization. Enter your exact hardware in the live app.
| GPU memory | Verdict | Best quant | VRAM | RAM | tok/s |
|---|---|---|---|---|---|
| 6 GB VRAM | Size unknown | – | – | – | – |
| 8 GB VRAM | Size unknown | – | – | – | – |
| 12 GB VRAM | Size unknown | – | – | – | – |
| 16 GB VRAM | Size unknown | – | – | – | – |
| 24 GB VRAM | Size unknown | – | – | – | – |
| 32 GB VRAM | Size unknown | – | – | – | – |
Parameter count unknown. The weights may not be on Hugging Face yet.
Benchmark results
Epoch AI has not published results for Ring-mini-linear-2.0 yet. New models are usually evaluated within days to weeks.
Links
More from Ant Group
Ring-2.6-1T · Ling-2.6-flash · Ring-flash-linear-2.0 · Ring-flash-2.0 · Ling-mini-base-2.0-20T · Ling-flash-base-2.0-20T · Agentar-Fin-R1 32B · Agentar-Fin-R1 8B