Ant Group
Ling 3.0 flash Fin
Ant Group model discovered on huggingface
Model Summary
Family
Ling
Version
3.0
Parameters
127.5B (est.)
Parameter counts for closed models are estimates; vendors rarely publish exact sizes.
VRAM Requirements by Quantization
Memory needed to serve Ling 3.0 flash Fin for inference, including a 20% overhead for activations and KV cache.
| Precision | VRAM needed | Smallest single GPU that fits |
|---|---|---|
| INT4 (4-bit) | 71.25 GB | NVIDIA H100 SXM5 (80 GB) |
| INT8 (8-bit) | 142.49 GB | NVIDIA B200 SXM (192 GB) |
| FP16 (16-bit) | 284.98 GB | NVIDIA B300 SXM (288 GB) |
| FP32 (32-bit) | 569.97 GB | Multi-GPU required |
Recommended GPU Configurations
Cheapest on-demand configurations to serve Ling 3.0 flash Fin at 8-bit (142 GB VRAM).
9x NVIDIA T4
144 GB total VRAM · Turing · multi-node
~$4.50/h
2x AMD Instinct MI250X
256 GB total VRAM · CDNA 2
~$5.00/h
9x NVIDIA P100 SXM2
144 GB total VRAM · Pascal · multi-node
~$5.40/h
Quick GPU Planning
Use the calculator pre-filled with this exact version to estimate memory, speed, and compute requirements in a few clicks.
Access Pre-filled CalculatorFrequently Asked Questions
How much VRAM do you need to run Ling 3.0 flash Fin?
With an estimated 127.5B parameters, Ling 3.0 flash Fin needs roughly 142 GB of VRAM in 8-bit (INT8), 71 GB in 4-bit, and 285 GB in FP16, including a 20% overhead for activations and KV cache.
Which GPUs can run Ling 3.0 flash Fin?
At 8-bit quantization, the most cost-effective option is 9x NVIDIA T4 (144 GB combined VRAM, around $4.50/hour on-demand). Higher-end cards like the NVIDIA B200 or AMD MI355X reduce the GPU count needed.
Can Ling 3.0 flash Fin run on a single GPU?
Yes. In 8-bit, a single NVIDIA B200 SXM (192 GB) fits the model.
How much does it cost to serve Ling 3.0 flash Fin in the cloud?
Renting 9x T4 costs on the order of $4.50/hour, i.e. about $3,285/month running 24/7. Actual prices vary by provider and commitment; spot and reserved capacity can be significantly cheaper.
Deploy on a GPU cloud
Rent 9x T4 by the hour instead of buying hardware.
