Nemotron 3.5 Bolt E4B on Arduino UNO Q (2 GB)
Can the Arduino UNO Q (2 GB) run Nemotron 3.5 Bolt E4B?
No, it doesn’t fit
No. Nemotron 3.5 Bolt E4B needs about 4.0 GB even at Q2_K; the Arduino UNO Q (2 GB) has 1.2 GB usable.
Download Nemotron 3.5 Bolt E4B
Recommended: Q2_K. 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 nemotron-3.5-bolt:e4bQuantized files · GGUF
Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.
Download the Q2_K (UD-Q2_K_XL) file (opens in a new tab)
huggingface.co/unsloth/NVIDIA-Nemotron-3.5-Bolt-E4B-GGUF (opens in a new tab)
ollama run hf.co/unsloth/NVIDIA-Nemotron-3.5-Bolt-E4B-GGUF:UD-Q2_K_XLOriginal weights · Hugging Face
Full-precision files from NVIDIA, for fine-tuning, vLLM, Transformers.
huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Bolt-E4B-BF16 (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 | 6.6 / 45 | |
|---|---|---|
| Memory fit | 0.0 / 25 | |
| Speed | 0.0 / 15 | |
| Memory use | 0.0 / 15 | |
| Match score | 6.6 / 100 |
Every quantization on the Arduino UNO Q (2 GB)
| Quant | Memory needed | Available | Speed | Runs | Quality | Download |
|---|---|---|---|---|---|---|
Q2_K | 4.0 GB | 1.2 GB | — | Won't run | 49Fair quality (C) · 49 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 6/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (UD-Q2_K_XL) (opens in a new tab) |
Q3_K_M | 4.8 GB | 1.2 GB | — | Won't run | 58Good quality (B) · 58 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 7/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (UD-Q3_K_XL) (opens in a new tab) |
Q4_K_M | 5.7 GB | 1.2 GB | — | Won't run | 66Good quality (B) · 66 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 8/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (UD-Q4_K_XL) (opens in a new tab) |
Q5_K_M | 6.5 GB | 1.2 GB | — | Won't run | 67Good quality (B) · 67 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 9/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (UD-Q5_K_XL) (opens in a new tab) |
Q6_K | 7.4 GB | 1.2 GB | — | Won't run | 69Good quality (B) · 69 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 9/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (UD-Q6_K_XL) (opens in a new tab) |
Q8_0 | 9.3 GB | 1.2 GB | — | Won't run | 70Great quality (A) · 70 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 9/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
F16 | 16.8 GB | 1.2 GB | — | Won't run | 70Great quality (A) · 70 of 100: how capable the model is at F16, whatever it runs on. Match score 9/100 (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
-
70Great quality (A) · 70 of 100: how capable the model is at F16, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking.
AMD Radeon RX 7900 XTX
-
70Great quality (A) · 70 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking.
Intel Arc B580
-
70Great quality (A) · 70 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 3060 12GB
-
70Great quality (A) · 70 of 100: how capable the model is at F16, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 3090
-
70Great quality (A) · 70 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4070 SUPER
-
70Great quality (A) · 70 of 100: how capable the model is at F16, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4090
Models that do run on the Arduino UNO Q (2 GB)
- 2Basic quality (D) · 2 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 56/100 (quality, fit, speed and memory use) sets the ranking. Falcon-H1 Tiny 90M Instruct
- 2Basic quality (D) · 2 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 55/100 (quality, fit, speed and memory use) sets the ranking. SmolLM2 135M Instruct
- 1Basic quality (D) · 1 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 55/100 (quality, fit, speed and memory use) sets the ranking. SmolLM 135M Instruct
- 7Basic quality (D) · 7 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 54/100 (quality, fit, speed and memory use) sets the ranking. LFM2.5 230M
- 9Basic quality (D) · 9 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 53/100 (quality, fit, speed and memory use) sets the ranking. LFM2.5 350M
Quick answers
How much memory does Nemotron 3.5 Bolt E4B need on the Arduino UNO Q 2GB?
Even at Q2_K it needs about 4.0 GB; the Arduino UNO Q 2GB has 1.2 GB usable.
What can the Arduino UNO Q 2GB run instead?
Falcon-H1 Tiny 90M Instruct, SmolLM2 135M Instruct and SmolLM 135M Instruct run best on it; the page lists more, each with its speed.
What hardware can run Nemotron 3.5 Bolt E4B?
RX 7900 XTX 24GB, Arc B580 12GB and RTX 3060 12GB 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.