JanusCoder 14B on AMD Ryzen AI Max+ 395 NAS (64 GB)
Can the AMD Ryzen AI Max+ 395 NAS (64 GB) run JanusCoder 14B?
Yes, it runs well
Runs well. At Q4_K_M it needs about 14.8 GB of 48.0 GB usable, with an estimated speed of 18.3 tok/s.
- Best quant
Q4_K_M- Generation speed
- 18.3 tok/s
- Prompt processing
- 2,493 tok/s
- First token (1K prompt)
- 0.4 s
- Largest safe context
- 32K
Best app to run it on the AMD Ryzen AI Max+ 395 NAS (64 GB)
On Linux
- Usually the first to support new model architectures.
llama-server -hf unsloth/JanusCoder-14B-GGUF:Q4_K_MDownload JanusCoder 14B
Recommended for the AMD Ryzen AI Max+ 395 NAS (64 GB): Q4_K_M. 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 Q4_K_M file (opens in a new tab)
huggingface.co/unsloth/JanusCoder-14B-GGUF (opens in a new tab)
ollama run hf.co/unsloth/JanusCoder-14B-GGUF:Q4_K_MOriginal weights · Hugging Face
Full-precision files from Shanghai AI Lab, for fine-tuning, vLLM, Transformers.
How 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 | 26.5 / 45 | |
|---|---|---|
| Memory fit | 25.0 / 25 | |
| Speed | 10.2 / 15 | |
| Memory use | 7.1 / 15 | |
| Match score | 68.8 / 100 |
Every quantization on the AMD Ryzen AI Max+ 395 NAS (64 GB)
| Quant | Memory needed | Available | Speed | Runs | Quality | Download |
|---|---|---|---|---|---|---|
Q2_K | 11.7 GB | 48.0 GB | 30.1 tok/s | Runs great | 43Fair quality (C) · 43 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 63/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q3_K_M | 13.0 GB | 48.0 GB | 23.7 tok/s | Runs well | 52Fair quality (C) · 52 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 (opens in a new tab) |
Q4_K_M | 14.8 GB | 48.0 GB | 18.3 tok/s | Runs well | 58Good quality (B) · 58 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 68/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q5_K_M | 16.3 GB | 48.0 GB | 15.1 tok/s | Runs well | 60Good quality (B) · 60 of 100: how capable the model is at Q5_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) |
Q6_K | 17.9 GB | 48.0 GB | 12.7 tok/s | Runs well | 61Good quality (B) · 61 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 69/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q8_0 | 21.4 GB | 48.0 GB | 9.3 tok/s | Slow | 62Good quality (B) · 62 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. | GGUF (opens in a new tab) |
F16 | 35.3 GB | 48.0 GB | 4.3 tok/s | Slow | 62Good quality (B) · 62 of 100: how capable the model is at F16, whatever it runs on. Match score 72/100 (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
-
62Good quality (B) · 62 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4090
-
62Good quality (B) · 62 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 3090
-
61Good quality (B) · 61 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking.
AMD Radeon RX 7900 XTX
-
60Good quality (B) · 60 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 82/100 (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 Q5_K_M, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4080 SUPER
-
60Good quality (B) · 60 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 5070 Ti
Quick answers
How much memory does JanusCoder 14B need on the AMD Ryzen AI Max+ 395 NAS 64GB?
At Q4_K_M it needs about 14.8 GB. The AMD Ryzen AI Max+ 395 NAS 64GB has 48.0 GB usable.
How fast is JanusCoder 14B on the AMD Ryzen AI Max+ 395 NAS 64GB?
About 18.3 tok/s at Q4_K_M, an estimate from the hardware’s memory bandwidth and the size of the model.
Which quantization of JanusCoder 14B should I use on the AMD Ryzen AI Max+ 395 NAS 64GB?
Q4_K_M. 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.