LFM2 700M on Intel Atom C3758 NAS (8 GB)
Can the Intel Atom C3758 NAS (8 GB) run LFM2 700M?
Yes, it runs great
Runs great. At Q3_K_M it needs about 1.5 GB of 5.2 GB usable, with an estimated speed of 40.0 tok/s.
- Best quant
Q3_K_M- Generation speed
- 40.0 tok/s
- Prompt processing
- 56.8 tok/s
- First token (1K prompt)
- 18.0 s
- Largest safe context
- 125K
Best app to run it on the Intel Atom C3758 NAS (8 GB)
Download LFM2 700M
Quantized files · GGUF
Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.
huggingface.co/LiquidAI/LFM2-700M-GGUF (opens in a new tab)
ollama run hf.co/LiquidAI/LFM2-700M-GGUFOriginal weights · Hugging Face
Full-precision files from Liquid AI, for fine-tuning, vLLM, Transformers.
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 | 6.8 / 45 | |
|---|---|---|
| Memory fit | 25.0 / 25 | |
| Speed | 15.0 / 15 | |
| Memory use | 6.6 / 15 | |
| Match score | 53.4 / 100 |
Every quantization on the Intel Atom C3758 NAS (8 GB)
| Quant | Memory needed | Available | Speed | Runs | Quality | Download |
|---|---|---|---|---|---|---|
Q2_K | 1.4 GB | 5.2 GB | 50.9 tok/s | Runs great | 12Basic quality (D) · 12 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 51/100 (quality, fit, speed and memory use) sets the ranking. | GGUF files (opens in a new tab) |
Q3_K_M | 1.5 GB | 5.2 GB | 40.0 tok/s | Runs great | 15Basic quality (D) · 15 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 53/100 (quality, fit, speed and memory use) sets the ranking. | GGUF files (opens in a new tab) |
Q4_K_M | 1.6 GB | 5.2 GB | 31.0 tok/s | Runs great | 17Basic quality (D) · 17 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 52/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q5_K_M | 1.6 GB | 5.2 GB | 25.6 tok/s | Runs well | 17Basic quality (D) · 17 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 52/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q6_K | 1.7 GB | 5.2 GB | 21.5 tok/s | Runs well | 17Basic quality (D) · 17 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 51/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q8_0 | 1.9 GB | 5.2 GB | 15.8 tok/s | Runs well | 18Basic quality (D) · 18 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 50/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
F16 | 2.6 GB | 5.2 GB | 7.3 tok/s | Slow | 18Basic quality (D) · 18 of 100: how capable the model is at F16, whatever it runs on. Match score 51/100 (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
-
18Basic quality (D) · 18 of 100: how capable the model is at F16, whatever it runs on. Match score 55/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4060
-
18Basic quality (D) · 18 of 100: how capable the model is at F16, whatever it runs on. Match score 54/100 (quality, fit, speed and memory use) sets the ranking.
Apple M4 (16 GB)
-
18Basic quality (D) · 18 of 100: how capable the model is at F16, whatever it runs on. Match score 53/100 (quality, fit, speed and memory use) sets the ranking.
Intel Arc B580
-
18Basic quality (D) · 18 of 100: how capable the model is at F16, whatever it runs on. Match score 53/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 3060 12GB
-
18Basic quality (D) · 18 of 100: how capable the model is at F16, whatever it runs on. Match score 53/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4070 SUPER
-
18Basic quality (D) · 18 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 53/100 (quality, fit, speed and memory use) sets the ranking.
Apple M1 (16 GB)
Quick answers
How much memory does LFM2 700M need on the Intel Atom C3758 NAS 8GB?
At Q3_K_M it needs about 1.5 GB. The Intel Atom C3758 NAS 8GB has 5.2 GB usable.
How fast is LFM2 700M on the Intel Atom C3758 NAS 8GB?
About 40.0 tok/s at Q3_K_M, an estimate from the hardware’s memory bandwidth and the size of the model.
Which quantization of LFM2 700M should I use on the Intel Atom C3758 NAS 8GB?
Q3_K_M. 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.