Ring-1T
Ring-1T is an open-weights language model from inclusionAI, released October 1, 2025. It has 1000B parameters (mixture-of-experts, 51B active). The context window is 125K tokens. API price: $0.57 input / $2.29 output per million tokens.
Today, we officially launch the trillion-parameter thinking model, Ring-1T. It is open-source upon release—developers can download the model weights from Hugging Face and ModelScope, or experience direct chat interactions and API calls via the Ling Chat page and ZenMux (links provided at the end of the article).
Check it against your own PC →
Can you run Ring-1T 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 | Too large | – | – | – | – |
| 8 GB VRAM | Too large | – | – | – | – |
| 12 GB VRAM | Too large | – | – | – | – |
| 16 GB VRAM | Too large | – | – | – | – |
| 24 GB VRAM | Too large | – | – | – | – |
| 32 GB VRAM | Too large | – | – | – | – |
Ready-made quantizations on Hugging Face: DevQuasar-3/inclusionAI.Ring-1T-GGUF · mradermacher/Ring-1T-i1-GGUF · ling1000T/Ring-1T-alibaba-gguf
Benchmark results
Epoch AI has not published results for Ring-1T yet. New models are usually evaluated within days to weeks.
Links
Announcement · Hugging Face: inclusionAI/Ring-1T
More from inclusionAI
Ling 3.1 flash 1019 · LBS 27B · Ling 3.0 flash Sante · Ling 3.0 tiny · Ling-1T