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Can the NVIDIA GeForce RTX 4060 Ti 16GB run Moonlight 16B-A3B Instruct?

75 ptsGreat (A) · 75 of 100 points: Model quality 20.1/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15

Yes, it runs well

Runs well. At Q5_K_M it needs about 13.0 GB of 16.0 GB usable, with an estimated speed of 48.7 tok/s.

Best quant
Q5_K_M
Generation speed
48.7 tok/s
Prompt processing
5,304 tok/s
First token (1K prompt)
0.3 s
Largest safe context
8K

Download Moonlight 16B-A3B Instruct

Original weights · Hugging Face

Full-precision files from Moonshot AI, for fine-tuning, vLLM, Transformers.

huggingface.co/moonshotai/Moonlight-16B-A3B-Instruct (opens in a new tab)

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

How the A grade is scored

Every result gets up to 100 points from four parts. The points decide the letter grade.

Model qualityEditorial quality tier of the model, scaled by the quantization or precision used.20.1 / 45
Memory fitFull marks when everything sits in GPU or unified memory; fewer when part spills to system RAM.25.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.15.0 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.15.0 / 15
Total75.1 / 10075 ptsGreat (A) · 75 of 100 points: Model quality 20.1/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15

Grade scale: S 85+ · A 72+ · B 58+ · C 42+ · D 25+ · F under 25 points.

Every quantization on the NVIDIA GeForce RTX 4060 Ti 16GB

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 8.0 GB 16.0 GB 96.8 tok/s Runs well 66 ptsGood (B) · 66 of 100 points: Model quality 14.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 11.6/15 All files (opens in a new tab)
Q3_K_M 9.5 GB 16.0 GB 76.2 tok/s Runs well 71 ptsGood (B) · 71 of 100 points: Model quality 17.4/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 13.7/15 All files (opens in a new tab)
Q4_K_M 11.4 GB 16.0 GB 58.9 tok/s Runs well 74 ptsGreat (A) · 74 of 100 points: Model quality 19.7/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 All files (opens in a new tab)
Q5_K_M 13.0 GB 16.0 GB 48.7 tok/s Runs well 75 ptsGreat (A) · 75 of 100 points: Model quality 20.1/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 All files (opens in a new tab)
Q6_K 14.7 GB 16.0 GB 40.9 tok/s Tight fit 74 ptsGreat (A) · 74 of 100 points: Model quality 20.5/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 All files (opens in a new tab)
Q8_0 18.6 GB 16.0 GB 19.9 tok/s Runs with offload 56 ptsUsable (C) · 56 of 100 points: Model quality 20.7/45, Memory fit 10.0/25, Speed 10.6/15, Memory use 15.0/15 All files (opens in a new tab)
F16 33.6 GB 16.0 GB 4.9 tok/s Heavy offload 44 ptsUsable (C) · 44 of 100 points: Model quality 20.7/45, Memory fit 4.0/25, Speed 5.2/15, Memory use 15.0/15 Original weights (opens in a new tab)

Memory figures assume 8K of context. Longer conversations or documents grow the KV cache.

Other hardware that runs it

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.