Ling-3.0-flash: hardware requirements
Ling-3.0-flash needs about 85 GB of memory at Q4_K_M quantization: a 79 GB download plus room for context and a runtime allowance. That fits a machine with 128GB RAM.
This is a mixture-of-experts model. Only a fraction of its 127B parameters are used for each token, so it runs faster than its size suggests, but all of it still has to fit in memory. The speed is that of a small model; the memory requirement is that of a large one. More on this →
Will it run on your machine?
Use it without your own hardware
OpenRouter lists Ling 3.0 Flash at $0.021 per million input tokens and $0.063 per million output tokens. Artificial Analysis measured hosted providers generating 356 tokens per second (Oct 10, 2026).
Price as listed on OpenRouter today. Speed is for hosted servers, not a home computer.
Download sizes by quantization
Lower quantization means a smaller file and less memory, at some cost to quality. Q4_K_M is the usual starting point. What is this?
| Quant | Download | RAM @ 4K | RAM @ 32K | Source |
|---|---|---|---|---|
| Q4_K_Mrecommended | 79 GB | 85 GB | 105 GB | AtomicChat/Ling-3.0-flash-GGUF |
| Q5_K_M | 89 GB | 95 GB | 115 GB | AtomicChat/Ling-3.0-flash-GGUF |
| Q6_K | 108 GB | 114 GB | 133 GB | AtomicChat/Ling-3.0-flash-GGUF |
| Q8_0 | 133 GB | 139 GB | 159 GB | AtomicChat/Ling-3.0-flash-GGUF |
| BF16 | 249 GB | 255 GB | 275 GB | AtomicChat/Ling-3.0-flash-GGUF |
Download sizes are measured from the published files named in the Source column. The RAM columns add the context cache, calculated from the model's configuration, and a runtime allowance of 10% of the download (at least 0.5GB, at most 3GB).