EXAONE 3.5 2.4B on Arduino UNO Q (2 GB)
Can the Arduino UNO Q (2 GB) run EXAONE 3.5 2.4B?
No, it doesn’t fit
No. EXAONE 3.5 2.4B needs about 2.3 GB even at Q2_K; the Arduino UNO Q (2 GB) has 1.2 GB usable.
Download EXAONE 3.5 2.4B
Quickest · Ollama
One command downloads a ready-to-run version and starts a chat.
ollama run exaone3.5:2.4bQuantized files · GGUF
Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.
huggingface.co/LGAI-EXAONE/EXAONE-3.5-2.4B-Instruct-GGUF (opens in a new tab)
ollama run hf.co/LGAI-EXAONE/EXAONE-3.5-2.4B-Instruct-GGUFOriginal weights · Hugging Face
Full-precision files from LG AI Research, for fine-tuning, vLLM, Transformers.
huggingface.co/LGAI-EXAONE/EXAONE-3.5-2.4B-Instruct (opens in a new tab)
Official repo · GitHub
Reference code, inference scripts and docs from LG AI Research. The weights themselves download from Hugging Face.
github.com/LG-AI-EXAONE/EXAONE-3.5 (opens in a new tab)
git clone https://github.com/LG-AI-EXAONE/EXAONE-3.5How 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 | 2.8 / 45 | |
|---|---|---|
| Memory fit | 0.0 / 25 | |
| Speed | 0.0 / 15 | |
| Memory use | 0.0 / 15 | |
| Match score | 2.8 / 100 |
Every quantization on the Arduino UNO Q (2 GB)
| Quant | Memory needed | Available | Speed | Runs | Quality | Download |
|---|---|---|---|---|---|---|
Q2_K | 2.3 GB | 1.2 GB | — | Won't run | 21Basic quality (D) · 21 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 2/100 (quality, fit, speed and memory use) sets the ranking. | GGUF files (opens in a new tab) |
Q3_K_M | 2.5 GB | 1.2 GB | — | Won't run | 25Basic quality (D) · 25 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 3/100 (quality, fit, speed and memory use) sets the ranking. | GGUF files (opens in a new tab) |
Q4_K_M | 2.8 GB | 1.2 GB | — | Won't run | 28Basic quality (D) · 28 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 3/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q5_K_M | 3.0 GB | 1.2 GB | — | Won't run | 29Basic quality (D) · 29 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 3/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q6_K | 3.3 GB | 1.2 GB | — | Won't run | 29Basic quality (D) · 29 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 4/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q8_0 | 3.9 GB | 1.2 GB | — | Won't run | 30Basic quality (D) · 30 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 4/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
F16 | 6.1 GB | 1.2 GB | — | Won't run | 30Basic quality (D) · 30 of 100: how capable the model is at F16, whatever it runs on. Match score 4/100 (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
-
30Basic quality (D) · 30 of 100: how capable the model is at F16, whatever it runs on. Match score 66/100 (quality, fit, speed and memory use) sets the ranking.
Intel Arc B580
-
30Basic quality (D) · 30 of 100: how capable the model is at F16, whatever it runs on. Match score 66/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 3060 12GB
-
30Basic quality (D) · 30 of 100: how capable the model is at F16, whatever it runs on. Match score 66/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4070 SUPER
-
30Basic quality (D) · 30 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 65/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4060
-
30Basic quality (D) · 30 of 100: how capable the model is at F16, whatever it runs on. Match score 63/100 (quality, fit, speed and memory use) sets the ranking.
AMD Radeon RX 9070 XT
-
30Basic quality (D) · 30 of 100: how capable the model is at F16, whatever it runs on. Match score 63/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4070 Ti SUPER
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 EXAONE 3.5 2.4B need on the Arduino UNO Q 2GB?
Even at Q2_K it needs about 2.3 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 EXAONE 3.5 2.4B?
Arc B580 12GB, RTX 3060 12GB and RTX 4070 SUPER 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.