MiniCPM5 2B on ZhaoXin KX-U6580 NAS (8 GB)
Can the ZhaoXin KX-U6580 NAS (8 GB) run MiniCPM5 2B?
Yes, it runs well
Runs well. At Q2_K it needs about 2.4 GB of 5.2 GB usable, with an estimated speed of 11.9 tok/s.
- Best quant
Q2_K- Generation speed
- 11.9 tok/s
- Prompt processing
- 9.9 tok/s
- First token (1K prompt)
- 103.2 s
- Largest safe context
- 72K
Best app to run it on the ZhaoXin KX-U6580 NAS (8 GB)
On Linux
- Usually the first to support new model architectures.
llama-server -hf openbmb/MiniCPM5-2B-GGUF:Q2_KDownload MiniCPM5 2B
Quantized files · GGUF
Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.
huggingface.co/openbmb/MiniCPM5-2B-GGUF (opens in a new tab)
ollama run hf.co/openbmb/MiniCPM5-2B-GGUFOriginal weights · Hugging Face
Full-precision files from OpenBMB, for fine-tuning, vLLM, Transformers.
Official repo · GitHub
Reference code, inference scripts and docs from OpenBMB. The weights themselves download from Hugging Face.
github.com/OpenBMB/MiniCPM (opens in a new tab)
git clone https://github.com/OpenBMB/MiniCPMHow it’s rated
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 quality | 18.9 / 45 | |
|---|---|---|
| Memory fit | 25.0 / 25 | |
| Speed | 8.2 / 15 | |
| Memory use | 10.5 / 15 | |
| Match score | 62.6 / 100 |
Every quantization on the ZhaoXin KX-U6580 NAS (8 GB)
| Quant | Memory needed | Available | Speed | Runs | Quality | Download |
|---|---|---|---|---|---|---|
Q2_K | 2.4 GB | 5.2 GB | 11.9 tok/s | Runs well | 42Fair quality (C) · 42 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 62/100 (quality, fit, speed and memory use) sets the ranking. | GGUF files (opens in a new tab) |
Q3_K_M | 2.6 GB | 5.2 GB | 9.3 tok/s | Slow | 50Fair quality (C) · 50 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 66/100 (quality, fit, speed and memory use) sets the ranking. | GGUF files (opens in a new tab) |
Q4_K_M | 2.9 GB | 5.2 GB | 7.2 tok/s | Slow | 57Good quality (B) · 57 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 69/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q5_K_M | 3.2 GB | 5.2 GB | 6.0 tok/s | Slow | 58Good quality (B) · 58 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 70/100 (quality, fit, speed and memory use) sets the ranking. | GGUF files (opens in a new tab) |
Q6_K | 3.4 GB | 5.2 GB | 5.0 tok/s | Slow | 59Good quality (B) · 59 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 72/100 (quality, fit, speed and memory use) sets the ranking. | GGUF files (opens in a new tab) |
Q8_0 | 4.0 GB | 5.2 GB | 3.7 tok/s | Slow | 60Good quality (B) · 60 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 71/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
F16 | 6.4 GB | 5.2 GB | 1.4 tok/s | Very slowfar over memory limit | 60Good quality (B) · 60 of 100: how capable the model is at F16, whatever it runs on. Match score 48/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) 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
-
60Good quality (B) · 60 of 100: how capable the model is at F16, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 3060 12GB
-
60Good quality (B) · 60 of 100: how capable the model is at F16, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4070 SUPER
-
60Good quality (B) · 60 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4060
-
60Good quality (B) · 60 of 100: how capable the model is at F16, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking.
AMD Radeon RX 9070 XT
-
60Good quality (B) · 60 of 100: how capable the model is at F16, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4070 Ti SUPER
-
60Good quality (B) · 60 of 100: how capable the model is at F16, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4080 SUPER
Quick answers
How much memory does MiniCPM5 2B need on the ZhaoXin KX-U6580 NAS 8GB?
At Q2_K it needs about 2.4 GB. The ZhaoXin KX-U6580 NAS 8GB has 5.2 GB usable.
How fast is MiniCPM5 2B on the ZhaoXin KX-U6580 NAS 8GB?
About 11.9 tok/s at Q2_K, an estimate from the hardware’s memory bandwidth and the size of the model.
Which quantization of MiniCPM5 2B should I use on the ZhaoXin KX-U6580 NAS 8GB?
Q2_K. 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.