Ant Group
Ling 3.0 flash VL
Ant Group model discovered on huggingface
Model Summary
Family
Ling
Version
3.0
Parameters
124.8B (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 VL for inference, including a 20% overhead for activations and KV cache.
| Precision | VRAM needed | Smallest single GPU that fits |
|---|---|---|
| INT4 (4-bit) | 69.74 GB | NVIDIA H100 SXM5 (80 GB) |
| INT8 (8-bit) | 139.47 GB | NVIDIA H200 SXM5 (141 GB) |
| FP16 (16-bit) | 278.95 GB | NVIDIA B300 SXM (288 GB) |
| FP32 (32-bit) | 557.90 GB | Multi-GPU required |
Recommended GPU Configurations
Cheapest on-demand configurations to serve Ling 3.0 flash VL at 8-bit (139 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 VL?
With an estimated 124.8B parameters, Ling 3.0 flash VL needs roughly 139 GB of VRAM in 8-bit (INT8), 70 GB in 4-bit, and 279 GB in FP16, including a 20% overhead for activations and KV cache.
Which GPUs can run Ling 3.0 flash VL?
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 VL run on a single GPU?
Yes. In 8-bit, a single NVIDIA H200 SXM5 (141 GB) fits the model.
How much does it cost to serve Ling 3.0 flash VL 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.
