Nemotron Content Safety Reasoning 4B on Arduino UNO Q (4 GB)
Can the Arduino UNO Q (4 GB) run Nemotron Content Safety Reasoning 4B?
No, it doesn’t fit
No. Nemotron Content Safety Reasoning 4B needs about 3.7 GB even at Q4_K_M; the Arduino UNO Q (4 GB) has 2.8 GB usable.
Download Nemotron Content Safety Reasoning 4B
Recommended: 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/DevQuasar/nvidia.Nemotron-Content-Safety-Reasoning-4B-GGUF (opens in a new tab)
ollama run hf.co/DevQuasar/nvidia.Nemotron-Content-Safety-Reasoning-4B-GGUF:Q4_K_MOriginal weights · Hugging Face
Full-precision files from NVIDIA, for fine-tuning, vLLM, Transformers.
huggingface.co/nvidia/Nemotron-Content-Safety-Reasoning-4B (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.
| Precision | 10.0 / 45 | |
|---|---|---|
| Memory fit | 0.0 / 25 | |
| Speed | 0.0 / 15 | |
| Clarity | 0.0 / 15 | |
| Match score | 10.0 / 100 |
Every quantization on the Arduino UNO Q (4 GB)
| Quant | Memory needed | Available | Speed | Runs | Quality | Download |
|---|---|---|---|---|---|---|
Q4_K_M | 3.7 GB | 2.8 GB | — | Won't run | 74Great quality (A) · 74 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 10/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q5_K_M | 4.2 GB | 2.8 GB | — | Won't run | 75Great quality (A) · 75 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 10/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q6_K | 4.6 GB | 2.8 GB | — | Won't run | 77Great quality (A) · 77 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 10/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q8_0 | 5.7 GB | 2.8 GB | — | Won't run | 78Great quality (A) · 78 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 10/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
F16 | 9.7 GB | 2.8 GB | — | Won't run | 78Great quality (A) · 78 of 100: how capable the model is at F16, whatever it runs on. Match score 10/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) Original weights (opens in a new tab) |
Times are for one request with a 512-token input and about 160 tokens written. Batching servers process many requests at once.
Hardware that can run it
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74Great quality (A) · 74 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA RTX PRO 6000 Blackwell
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74Great quality (A) · 74 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 5090
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75Great quality (A) · 75 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA B200
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74Great quality (A) · 74 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.
AMD Instinct MI350X
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74Great quality (A) · 74 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 81/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GB300 Grace Blackwell Ultra Desktop Superchip
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74Great quality (A) · 74 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 81/100 (quality, fit, speed and memory use) sets the ranking.
AMD Instinct MI325X
Models that do run on the Arduino UNO Q (4 GB)
- 86Excellent quality (A+) · 86 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. Jina Reranker v3.5
- 84Great quality (A) · 84 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. Jina Reranker v3
- 80Great quality (A) · 80 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. GLiNER2.5 Decide
- 81Great quality (A) · 81 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking. mxbai-rerank-large v2
- 80Great quality (A) · 80 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking. FRIDA-Decisions
Quick answers
How much memory does Nemotron Content Safety Reasoning 4B need on the Arduino UNO Q 4GB?
Even at Q4_K_M it needs about 3.7 GB; the Arduino UNO Q 4GB has 2.8 GB usable.
What can the Arduino UNO Q 4GB run instead?
Jina Reranker v3.5, Jina Reranker v3 and GLiNER2.5 Decide run best on it; the page lists more, each with its speed.
What hardware can run Nemotron Content Safety Reasoning 4B?
NVIDIA RTX PRO 6000 Blackwell 96GB, RTX 5090 32GB and NVIDIA B200 180GB 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.