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LLMs ·

Ling Mini 2.0 (16B-A1.4B)

Parameters
16B (1.4B active)
Architecture
Mixture of experts
Max context
32K tokens
License
mit
Released
2025-09

How to run it

Quantized files · GGUF

Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.

huggingface.co/inclusionAI/Ling-mini-2.0-GGUF (opens in a new tab)

ollama run hf.co/inclusionAI/Ling-mini-2.0-GGUF

Original weights · Hugging Face

Full-precision files from Ant Group (inclusionAI), for fine-tuning, vLLM, Transformers.

huggingface.co/inclusionAI/Ling-mini-2.0 (opens in a new tab)

No sign-in needed.

Official repo · GitHub

Reference code, inference scripts and docs from Ant Group (inclusionAI). The weights themselves download from Hugging Face.

github.com/inclusionAI/Ling-V2 (opens in a new tab)

git clone https://github.com/inclusionAI/Ling-V2

Links checked 7 days ago against Hugging Face, Ollama and GitHub.

Memory needed

Weights plus KV cache and runtime overhead. Leave a little extra free for the operating system and other apps.

Quantization Quality Weights Total at 8K context Total at 32K context Download
Q2_K Low 6.5 GB 7.4 GB 8.4 GB GGUF (opens in a new tab)
Q3_K_M Low 8.0 GB 8.9 GB 9.9 GB GGUF files (opens in a new tab)
Q4_K_M Good 9.9 GB 10.9 GB 11.9 GB GGUF (opens in a new tab)
Q5_K_M High 11.5 GB 12.5 GB 13.5 GB GGUF files (opens in a new tab)
Q6_K High 13.3 GB 14.3 GB 15.3 GB GGUF (opens in a new tab)
Q8_0 Very high 17.2 GB 18.2 GB 19.2 GB GGUF (opens in a new tab)
F16 Full 32.5 GB 33.5 GB 34.5 GB GGUF (opens in a new tab) Original weights (opens in a new tab)

Best hardware for Ling Mini 2.0 (16B-A1.4B)

The least expensive GPU in our catalog that runs it without offloading is the Intel Arc A580 (launch price $179) at Q2_K.

Grade · points Hardware Quant Memory Speed Fit
78 ptsGreat (A) · 78 of 100 points: Model quality 23.4/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 AMD Radeon RX 7900 XTX Q8_0 19.4 GB / 24.0 GB 184 tok/s Runs well
78 ptsGreat (A) · 78 of 100 points: Model quality 23.4/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 Apple M4 Max (64 GB) F16 37.3 GB / 48.0 GB 48.4 tok/s Runs well
78 ptsGreat (A) · 78 of 100 points: Model quality 23.4/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 3090 Q8_0 19.4 GB / 24.0 GB 209 tok/s Runs well
78 ptsGreat (A) · 78 of 100 points: Model quality 23.4/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 4090 Q8_0 19.4 GB / 24.0 GB 225 tok/s Runs well
77 ptsGreat (A) · 77 of 100 points: Model quality 22.7/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 AMD Radeon RX 9070 XT Q5_K_M 13.3 GB / 16.0 GB 200 tok/s Runs well
77 ptsGreat (A) · 77 of 100 points: Model quality 22.7/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 4060 Ti 16GB Q5_K_M 13.3 GB / 16.0 GB 104 tok/s Runs well
77 ptsGreat (A) · 77 of 100 points: Model quality 22.7/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 4070 Ti SUPER Q5_K_M 13.3 GB / 16.0 GB 243 tok/s Runs well
77 ptsGreat (A) · 77 of 100 points: Model quality 22.7/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 4080 SUPER Q5_K_M 13.3 GB / 16.0 GB 267 tok/s Runs well
77 ptsGreat (A) · 77 of 100 points: Model quality 22.7/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 5060 Ti 16GB Q5_K_M 13.3 GB / 16.0 GB 162 tok/s Runs well
77 ptsGreat (A) · 77 of 100 points: Model quality 22.7/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 5070 Ti Q5_K_M 13.3 GB / 16.0 GB 325 tok/s Runs well

Check it on your own hardware

Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.