gpt-oss 120B on AMD Ryzen 5 7640HS NAS (16 GB)
Can the AMD Ryzen 5 7640HS NAS (16 GB) run gpt-oss 120B?
No, it doesn’t fit
No. gpt-oss 120B needs about 68.5 GB even at MXFP4; the AMD Ryzen 5 7640HS NAS (16 GB) has 12.0 GB usable.
Download gpt-oss 120B
Recommended: MXFP4. Every other quantization has its own download link in the table below.
Quickest · Ollama
One command downloads a ready-to-run version and starts a chat.
ollama run gpt-oss:120bQuantized files · GGUF
Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.
Download the MXFP4 file (opens in a new tab)
huggingface.co/ggml-org/gpt-oss-120b-GGUF (opens in a new tab)
ollama run hf.co/ggml-org/gpt-oss-120b-GGUF:MXFP4Original weights · Hugging Face
Full-precision files from OpenAI, for fine-tuning, vLLM, Transformers.
Official repo · GitHub
Reference code, inference scripts and docs from OpenAI. The weights themselves download from Hugging Face.
github.com/openai/gpt-oss (opens in a new tab)
git clone https://github.com/openai/gpt-ossHow 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 | 11.3 / 45 | |
|---|---|---|
| Memory fit | 0.0 / 25 | |
| Speed | 0.0 / 15 | |
| Memory use | 0.0 / 15 | |
| Match score | 11.3 / 100 |
Every quantization on the AMD Ryzen 5 7640HS NAS (16 GB)
| Quant | Memory needed | Available | Speed | Runs | Quality | Download |
|---|---|---|---|---|---|---|
MXFP4 | 68.5 GB | 12.0 GB | — | Won't run | 84Great quality (A) · 84 of 100: how capable the model is at MXFP4, whatever it runs on. Match score 11/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) Original weights (opens in a new tab) |
F16 | 235 GB | 12.0 GB | — | Won't run | 84Great quality (A) · 84 of 100: how capable the model is at F16, whatever it runs on. Match score 11/100 (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.
Hardware that can run it
-
84Great quality (A) · 84 of 100: how capable the model is at MXFP4, whatever it runs on. Match score 92/100 (quality, fit, speed and memory use) sets the ranking.
AMD Ryzen AI Max+ 395 (128 GB)
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84Great quality (A) · 84 of 100: how capable the model is at MXFP4, whatever it runs on. Match score 92/100 (quality, fit, speed and memory use) sets the ranking.
Apple M4 Max (128 GB)
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84Great quality (A) · 84 of 100: how capable the model is at MXFP4, whatever it runs on. Match score 92/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GB10 (128 GB)
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84Great quality (A) · 84 of 100: how capable the model is at MXFP4, whatever it runs on. Match score 92/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA RTX PRO 6000 Blackwell
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84Great quality (A) · 84 of 100: how capable the model is at MXFP4, whatever it runs on. Match score 92/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA RTX Spark N1X (6144-core GPU) (128 GB)
-
84Great quality (A) · 84 of 100: how capable the model is at MXFP4, whatever it runs on. Match score 90/100 (quality, fit, speed and memory use) sets the ranking.
Apple M2 Ultra (192 GB)
Models that do run on the AMD Ryzen 5 7640HS NAS (16 GB)
- 66Good quality (B) · 66 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking. Mellum2.1 Thinking (12B-A2.5B)
- 58Good quality (B) · 58 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. Maple Preview (20B-A1B)
- 58Good quality (B) · 58 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. Ling 3.0 Tiny (8B-A1.3B)
- 51Fair quality (C) · 51 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. LFM2.5 24B-A2B
- 66Good quality (B) · 66 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. Nemotron 3.5 Bolt E4B
Quick answers
How much memory does gpt-oss 120B need on the AMD Ryzen 5 7640HS NAS 16GB?
Even at MXFP4 it needs about 68.5 GB; the AMD Ryzen 5 7640HS NAS 16GB has 12.0 GB usable.
What can the AMD Ryzen 5 7640HS NAS 16GB run instead?
Mellum2.1 Thinking (12B-A2.5B), Maple Preview (20B-A1B) and Ling 3.0 Tiny (8B-A1.3B) run best on it; the page lists more, each with its speed.
What hardware can run gpt-oss 120B?
AMD Ryzen AI Max+ 395 128GB, M4 Max 128GB and NVIDIA GB10 128GB run it; the page lists more, each with its speed.
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.