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Can the ZhaoXin KX-U6580 NAS (64 GB) run LLM4Decompile 22B V2?

58Good quality (B) · 58 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 65/100 (quality, fit, speed and memory use) sets the ranking.

Barely: it runs very slowly

Very slow. At Q8_0 it needs about 30.4 GB of 54.4 GB usable, with an estimated speed of 0.4 tok/s.

Best quant
Q8_0
Generation speed
0.4 tok/s
Prompt processing
1.1 tok/s
First token (1K prompt)
911.4 s
Largest safe context
32K

Best app to run it on the ZhaoXin KX-U6580 NAS (64 GB)

On Linux

llama.cpp

Command line + local API · runs on llama.cpp

  • Usually the first to support new model architectures.
llama-server -hf mradermacher/llm4decompile-22b-v2-GGUF:Q8_0

How we choose: the files published for this model, which apps run in a container on a NAS without a graphics card (models run on its processor), and whether the model fits fully in the memory models can use. Details.

Download LLM4Decompile 22B V2

Recommended for the ZhaoXin KX-U6580 NAS (64 GB): Q8_0. Every other quantization has its own download link in the table below.

Quantized files · GGUF

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

Download the Q8_0 file (opens in a new tab)

huggingface.co/mradermacher/llm4decompile-22b-v2-GGUF (opens in a new tab)

ollama run hf.co/mradermacher/llm4decompile-22b-v2-GGUF:Q8_0

Original weights · Hugging Face

Full-precision files from LLM4Binary, for fine-tuning, vLLM, Transformers.

huggingface.co/LLM4Binary/llm4decompile-22b-v2 (opens in a new tab)

No sign-in needed.

Official repo · GitHub

Reference code, inference scripts and docs from LLM4Binary. The weights themselves download from Hugging Face.

github.com/albertan017/LLM4Decompile (opens in a new tab)

Official code and the Ghidra script that feeds decompiler output to the V2 models.

git clone https://github.com/albertan017/LLM4Decompile

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

How it’s rated

Quality 58Good quality (B) · 58 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 65/100 (quality, fit, speed and memory use) sets the ranking.
How capable the model itself is at Q8_0, 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 Very slow
How well it runs on the ZhaoXin KX-U6580 NAS (64 GB): 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.26.1 / 45
Memory fitFull marks when the model fits in the share of the NAS’s memory that models can use (the rest stays with the NAS system and its storage services); fewer when it goes past that limit.25.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.1.5 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.12.9 / 15
Match score65.5 / 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 ZhaoXin KX-U6580 NAS (64 GB)

Quant Memory needed Available Speed Runs Quality Download
Q2_K 15.7 GB 54.4 GB 1.3 tok/s Very slow 40Fair quality (C) · 40 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 52/100 (quality, fit, speed and memory use) sets the ranking. GGUF (opens in a new tab)
Q3_K_M 17.7 GB 54.4 GB 1.1 tok/s Very slow 48Fair quality (C) · 48 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 56/100 (quality, fit, speed and memory use) sets the ranking. GGUF (opens in a new tab)
Q4_K_M 20.4 GB 54.4 GB 0.8 tok/s Very slow 55Good quality (B) · 55 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 60/100 (quality, fit, speed and memory use) sets the ranking. GGUF (opens in a new tab)
Q5_K_M 22.6 GB 54.4 GB 0.7 tok/s Very slow 56Good quality (B) · 56 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 61/100 (quality, fit, speed and memory use) sets the ranking. GGUF (opens in a new tab)
Q6_K 25.1 GB 54.4 GB 0.6 tok/s Very slow 57Good quality (B) · 57 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 63/100 (quality, fit, speed and memory use) sets the ranking. GGUF (opens in a new tab)
Q8_0 30.4 GB 54.4 GB 0.4 tok/s Very slow 58Good quality (B) · 58 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 65/100 (quality, fit, speed and memory use) sets the ranking. GGUF (opens in a new tab)
F16 51.3 GB 54.4 GB 0.2 tok/s Very slowtight fit 58Good quality (B) · 58 of 100: how capable the model is at F16, whatever it runs on. Match score 66/100 (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 LLM4Decompile 22B V2 need on the ZhaoXin KX-U6580 NAS 64GB?

At Q8_0 it needs about 30.4 GB. The ZhaoXin KX-U6580 NAS 64GB has 54.4 GB usable.

How fast is LLM4Decompile 22B V2 on the ZhaoXin KX-U6580 NAS 64GB?

About 0.4 tok/s at Q8_0, an estimate from the hardware’s memory bandwidth and the size of the model.

Which quantization of LLM4Decompile 22B V2 should I use on the ZhaoXin KX-U6580 NAS 64GB?

Q8_0. 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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