Ling-3.1-flash-1019
Ling-3.1-flash-1019 loads in 358 GB at Q4_K_M and decodes at the speed of its 25B active path, comfortably from 256 GB of memory. Below is the memory math we ran for it, the smallest card that fits, and the fastest machine we track.
- Parameters
- 560B(25B active)
- Format
- Q4_K_M
- Min memory
- 512 GB
- Best for
- Reasoning, Agents, Long context
How much memory does Ling-3.1-flash-1019 need?
Ling-3.1-flash-1019 is a 560B mixture-of-experts model (25B active per token) built for reasoning, agents, long context. The weights alone take 358 GB at Q4_K_M; add context and the OS, and it belongs in the 256 GB memory class. Every number below comes from the ModelFit engine: speeds are estimates, labeled est., because we do not benchmark hardware ourselves.
Run with llama.cpp: llama-server -hf bartowski/Ling-3.1-flash-1019-GGUF:Q4_K_M.
KV = fp16 estimate (q8_0 cache roughly halves it). "Comfortable" = weights + KV within the engine's tiered budget (~70-85% of memory).
Which machines run Ling-3.1-flash-1019?
- Smallest GPU
- n/ano consumer fit
- Fastest
- n/an/a
- Runs on a Mac?
- Nobeyond current Macs
Verdicts come from the same engine that powers our fit checker: memory capacity first, bandwidth for speed. How we compute these numbers · What typical error means · Hugging Face model card
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Frequently asked questions
How much memory does Ling-3.1-flash-1019 need?
358 GB for the Q4_K_M weights, plus ~6.0 GB of KV-cache at 16k context, about 364.0 GB total. Comfortable from 256 GB of VRAM or unified memory.
Does Ling-3.1-flash-1019 run on a Mac?
Not on the current Mac configs we track; Ling-3.1-flash-1019 needs more memory than they offer.
What is the smallest GPU for Ling-3.1-flash-1019?
No tracked consumer GPU runs Ling-3.1-flash-1019 comfortably.
Cite this page
ModelFit: Ling-3.1-flash-1019, specs, memory math and hardware verdicts. https://modelfit.io/models/ling-3.1-flash-1019 (dataset updated 2026-10-30, CC BY 4.0).