Pixtral 12B (2409) on Intel Atom C3538 / C3558 NAS (16 GB)
Can the Intel Atom C3538 / C3558 NAS (16 GB) run Pixtral 12B (2409)?
Barely: it runs very slowly (tight fit)
Very slow (tight fit). At Q5_K_M it needs about 11.7 GB of 12.0 GB usable, with an estimated speed of 0.7 tok/s.
- Best quant
Q5_K_M- Generation speed
- 0.7 tok/s
- Prompt processing
- 1.5 tok/s
- First token (1K prompt)
- 705.4 s
- Largest safe context
- 9K
Download Pixtral 12B (2409)
Original weights · Hugging Face
Full-precision files from Mistral AI, for fine-tuning, vLLM, Transformers.
huggingface.co/mistralai/Pixtral-12B-2409 (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 | 21.8 / 45 | |
|---|---|---|
| Memory fit | 24.0 / 25 | |
| Speed | 1.9 / 15 | |
| Memory use | 15.0 / 15 | |
| Match score | 62.7 / 100 |
Every quantization on the Intel Atom C3538 / C3558 NAS (16 GB)
| Quant | Memory needed | Available | Speed | Runs | Quality | Download |
|---|---|---|---|---|---|---|
Q2_K | 7.9 GB | 12.0 GB | 1.3 tok/s | Very slow | 35Basic quality (D) · 35 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 58/100 (quality, fit, speed and memory use) sets the ranking. | All files (opens in a new tab) |
Q3_K_M | 9.0 GB | 12.0 GB | 1.0 tok/s | Very slow | 42Fair quality (C) · 42 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 61/100 (quality, fit, speed and memory use) sets the ranking. | All files (opens in a new tab) |
Q4_K_M | 10.5 GB | 12.0 GB | 0.8 tok/s | Very slowtight fit | 47Fair quality (C) · 47 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 62/100 (quality, fit, speed and memory use) sets the ranking. | All files (opens in a new tab) |
Q5_K_M | 11.7 GB | 12.0 GB | 0.7 tok/s | Very slowtight fit | 48Fair quality (C) · 48 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 62/100 (quality, fit, speed and memory use) sets the ranking. | All files (opens in a new tab) |
Q6_K | 13.1 GB | 12.0 GB | 0.5 tok/s | Very slowover memory limit | 49Fair quality (C) · 49 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 48/100 (quality, fit, speed and memory use) sets the ranking. | All files (opens in a new tab) |
Q8_0 | 16.0 GB | 12.0 GB | — | Won't run | 50Fair quality (C) · 50 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 6/100 (quality, fit, speed and memory use) sets the ranking. | All files (opens in a new tab) |
F16 | 27.7 GB | 12.0 GB | — | Won't run | 50Fair quality (C) · 50 of 100: how capable the model is at F16, whatever it runs on. Match score 6/100 (quality, fit, speed and memory use) sets the ranking. | 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
-
50Fair quality (C) · 50 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.
AMD Radeon RX 7900 XTX
-
50Fair quality (C) · 50 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.
NVIDIA GeForce RTX 3090
-
50Fair quality (C) · 50 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.
NVIDIA GeForce RTX 4090
-
49Fair quality (C) · 49 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4070 Ti SUPER
-
49Fair quality (C) · 49 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4080 SUPER
-
49Fair quality (C) · 49 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 5070 Ti
Quick answers
How much memory does Pixtral 12B (2409) need on the Intel Atom C3538 / C3558 NAS 16GB?
At Q5_K_M it needs about 11.7 GB. The Intel Atom C3538 / C3558 NAS 16GB has 12.0 GB usable.
How fast is Pixtral 12B (2409) on the Intel Atom C3538 / C3558 NAS 16GB?
About 0.7 tok/s at Q5_K_M, an estimate from the hardware’s memory bandwidth and the size of the model.
Which quantization of Pixtral 12B (2409) should I use on the Intel Atom C3538 / C3558 NAS 16GB?
Q5_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.