OpenReasoning Nemotron 7B on AMD Ryzen 7 3700X / 5 3600 NAS (128 GB)
Can the AMD Ryzen 7 3700X / 5 3600 NAS (128 GB) run OpenReasoning Nemotron 7B?
Yes, it runs well
Runs well. At Q2_K it needs about 13.1 GB of 113 GB usable, with an estimated speed of 10.3 tok/s.
- Best quant
Q2_K- Generation speed
- 10.3 tok/s
- Prompt processing
- 28.9 tok/s
- First token (1K prompt)
- 35.5 s
- Largest safe context
- 128K
Best app to run it on the AMD Ryzen 7 3700X / 5 3600 NAS (128 GB)
On Linux
- Usually the first to support new model architectures.
llama-server -hf bartowski/nvidia_OpenReasoning-Nemotron-7B-GGUF:Q2_KDownload OpenReasoning Nemotron 7B
Recommended for the AMD Ryzen 7 3700X / 5 3600 NAS (128 GB): Q2_K. 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 Q2_K file (opens in a new tab)
huggingface.co/bartowski/nvidia_OpenReasoning-Nemotron-7B-GGUF (opens in a new tab)
ollama run hf.co/bartowski/nvidia_OpenReasoning-Nemotron-7B-GGUF:Q2_KOriginal weights · Hugging Face
Full-precision files from NVIDIA, for fine-tuning, vLLM, Transformers.
huggingface.co/nvidia/OpenReasoning-Nemotron-7B (opens in a new tab)
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 | 17.0 / 45 | |
|---|---|---|
| Memory fit | 25.0 / 25 | |
| Speed | 7.6 / 15 | |
| Memory use | 2.7 / 15 | |
| Match score | 52.3 / 100 |
Every quantization on the AMD Ryzen 7 3700X / 5 3600 NAS (128 GB)
| Quant | Memory needed | Available | Speed | Runs | Quality | Download |
|---|---|---|---|---|---|---|
Q2_K | 13.1 GB | 113 GB | 10.3 tok/s | Runs well | 37Basic quality (D) · 37 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 | 13.8 GB | 113 GB | 8.1 tok/s | Slow | 45Fair quality (C) · 45 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 55/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q4_K_M | 14.7 GB | 113 GB | 6.3 tok/s | Slow | 51Fair quality (C) · 51 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 57/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q5_K_M | 15.5 GB | 113 GB | 5.2 tok/s | Slow | 52Fair quality (C) · 52 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 57/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q6_K | 16.3 GB | 113 GB | 4.4 tok/s | Slow | 53Fair quality (C) · 53 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 57/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q8_0 | 18.2 GB | 113 GB | 3.2 tok/s | Slow | 54Fair quality (C) · 54 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 57/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
F16 | 25.3 GB | 113 GB | 1.5 tok/s | Very slow | 54Fair quality (C) · 54 of 100: how capable the model is at F16, whatever it runs on. Match score 57/100 (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
-
54Fair quality (C) · 54 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4070 SUPER
-
53Fair quality (C) · 53 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 3060 12GB
-
53Fair quality (C) · 53 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking.
Intel Arc B580
-
54Fair quality (C) · 54 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.
AMD Radeon RX 9070 XT
-
54Fair quality (C) · 54 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 4070 Ti SUPER
-
54Fair quality (C) · 54 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 4080 SUPER
Quick answers
How much memory does OpenReasoning Nemotron 7B need on the AMD Ryzen 7 3700X / 5 3600 NAS 128GB?
At Q2_K it needs about 13.1 GB. The AMD Ryzen 7 3700X / 5 3600 NAS 128GB has 113 GB usable.
How fast is OpenReasoning Nemotron 7B on the AMD Ryzen 7 3700X / 5 3600 NAS 128GB?
About 10.3 tok/s at Q2_K, an estimate from the hardware’s memory bandwidth and the size of the model.
Which quantization of OpenReasoning Nemotron 7B should I use on the AMD Ryzen 7 3700X / 5 3600 NAS 128GB?
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.