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Can the AMD Radeon PRO W7800 48GB run Moonlight 16B-A3B Instruct?

46Fair quality (C) · 46 of 100: how capable the model is at F16, whatever it runs on. Match score 75/100 (quality, fit, speed and memory use) sets the ranking.

Yes, it runs great

Runs great. At F16 it needs about 35.2 GB of 48.0 GB usable, with an estimated speed of 54.4 tok/s.

Best quant
F16
Generation speed
54.4 tok/s
Prompt processing
18,683 tok/s
First token (1K prompt)
0.3 s
Largest safe context
8K

Best app to run it on the AMD Radeon PRO W7800 48GB

On Windows

Docker Model Runner

Command line + local API · runs on llama.cpp, vLLM

  • Handy if you already work in Docker.
docker model run hf.co/moonshotai/Moonlight-16B-A3B-Instruct

On Linux

Docker Model Runner

Command line + local API · runs on llama.cpp, vLLM

  • Handy if you already work in Docker.
docker model run hf.co/moonshotai/Moonlight-16B-A3B-Instruct

How we choose: the files published for this model, your operating system and GPU, whether it fits fully in memory, and published speed tests (MLX vs llama.cpp on Apple silicon, vLLM vs llama.cpp vs Ollama on NVIDIA). Details.

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)

No sign-in needed.

Links checked 3 days ago against Hugging Face, Ollama and GitHub.

How it’s rated

Quality 46Fair quality (C) · 46 of 100: how capable the model is at F16, whatever it runs on. Match score 75/100 (quality, fit, speed and memory use) sets the ranking.
How capable the model itself is at F16, from its editorial quality tier scaled by the quantization or precision. It’s the same on any hardware that runs this variant. Scale: A+ 85+ · A 70+ · B 55+ · C 40+ · D under 40.
Runs Runs great
How well it runs on the AMD Radeon PRO W7800 48GB: speed, capped by how well it fits in memory. Runs great: 30+ tokens/s (or near the image, video or decision speed target) · Runs well: 10+ tokens/s · Slow: 3+ tokens/s · Very slow: under 3 · Won’t run: doesn’t fit even with offload. A tight fit or RAM offload caps it at Runs well; heavy offload caps it at Slow.

Match score

To order lists, each result also gets a match score out of 100 from four parts. It favors the most capable model that still runs well.

Model qualityEditorial quality tier of the model, scaled by the quantization or precision used.20.7 / 45
Memory fitFull marks when everything sits in GPU 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
Match score75.7 / 100

The match score orders results; it is not shown as a grade. Quality and Runs are the two ratings in the tables.

Every quantization on the AMD Radeon PRO W7800 48GB

Quant Memory needed Available Speed Runs Quality Download
Q2_K 9.6 GB 48.0 GB 195 tok/s Runs great 32Basic quality (D) · 32 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 59/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
Q3_K_M 11.1 GB 48.0 GB 173 tok/s Runs great 38Basic quality (D) · 38 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 62/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
Q4_K_M 13.0 GB 48.0 GB 150 tok/s Runs great 43Fair quality (C) · 43 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 65/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
Q5_K_M 14.6 GB 48.0 GB 134 tok/s Runs great 44Fair quality (C) · 44 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 67/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
Q6_K 16.3 GB 48.0 GB 120 tok/s Runs great 45Fair quality (C) · 45 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 68/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
Q8_0 20.2 GB 48.0 GB 97.5 tok/s Runs great 46Fair quality (C) · 46 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 70/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
F16 35.2 GB 48.0 GB 54.4 tok/s Runs great 46Fair quality (C) · 46 of 100: how capable the model is at F16, whatever it runs on. Match score 75/100 (quality, fit, speed and memory use) sets the ranking. 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

Quick answers

How much memory does Moonlight 16B-A3B Instruct need on the PRO W7800 48GB?

At F16 it needs about 35.2 GB. The PRO W7800 48GB has 48.0 GB usable.

How fast is Moonlight 16B-A3B Instruct on the PRO W7800 48GB?

About 54.4 tok/s at F16, an estimate from the hardware’s memory bandwidth and the size of the model.

Which quantization of Moonlight 16B-A3B Instruct should I use on the PRO W7800 48GB?

F16. Of the versions that fit, it is the one that runs best; when two run equally well, the check prefers the higher-rated one.

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.

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