Magistral Small 2507 on AMD Ryzen Embedded R2514 / R2544 NAS (64 GB)
Can the AMD Ryzen Embedded R2514 / R2544 NAS (64 GB) run Magistral Small 2507?
Barely: it runs very slowly
Very slow. At Q8_0 it needs about 31.3 GB of 54.4 GB usable, with an estimated speed of 0.4 tok/s.
- Best quant
Q8_0- Generation speed
- 0.4 tok/s
- Prompt processing
- 2.5 tok/s
- First token (1K prompt)
- 402.3 s
- Largest safe context
- 40K
Best app to run it on the AMD Ryzen Embedded R2514 / R2544 NAS (64 GB)
Download Magistral Small 2507
Recommended for the AMD Ryzen Embedded R2514 / R2544 NAS (64 GB): Q8_0. 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 Q8_0 file (opens in a new tab)
huggingface.co/mistralai/Magistral-Small-2507-GGUF (opens in a new tab)
ollama run hf.co/mistralai/Magistral-Small-2507-GGUF:Q8_0Original weights · Hugging Face
Full-precision files from Mistral AI, for fine-tuning, vLLM, Transformers.
huggingface.co/mistralai/Magistral-Small-2507 (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 | 31.5 / 45 | |
|---|---|---|
| Memory fit | 25.0 / 25 | |
| Speed | 1.5 / 15 | |
| Memory use | 13.3 / 15 | |
| Match score | 71.3 / 100 |
Every quantization on the AMD Ryzen Embedded R2514 / R2544 NAS (64 GB)
| Quant | Memory needed | Available | Speed | Runs | Quality | Download |
|---|---|---|---|---|---|---|
Q2_K | 15.7 GB | 54.4 GB | 1.3 tok/s | Very slow | 49Fair quality (C) · 49 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 56/100 (quality, fit, speed and memory use) sets the ranking. | GGUF files (opens in a new tab) |
Q3_K_M | 17.8 GB | 54.4 GB | 1.0 tok/s | Very slow | 58Good quality (B) · 58 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. | GGUF files (opens in a new tab) |
Q4_K_M | 20.7 GB | 54.4 GB | 0.8 tok/s | Very slow | 66Good quality (B) · 66 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 65/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q5_K_M | 23.0 GB | 54.4 GB | 0.6 tok/s | Very slow | 67Good quality (B) · 67 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 67/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q6_K | 25.6 GB | 54.4 GB | 0.5 tok/s | Very slow | 69Good quality (B) · 69 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 68/100 (quality, fit, speed and memory use) sets the ranking. | GGUF files (opens in a new tab) |
Q8_0 | 31.3 GB | 54.4 GB | 0.4 tok/s | Very slow | 70Great quality (A) · 70 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 71/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
F16 | 53.4 GB | 54.4 GB | 0.2 tok/s | Very slowtight fit | 70Great quality (A) · 70 of 100: how capable the model is at F16, whatever it runs on. Match score 71/100 (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
-
69Good quality (B) · 69 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 5090
-
67Good quality (B) · 67 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 85/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 3090
-
67Good quality (B) · 67 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 85/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4090
-
66Good quality (B) · 66 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 84/100 (quality, fit, speed and memory use) sets the ranking.
AMD Radeon RX 7900 XTX
-
58Good quality (B) · 58 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4070 Ti SUPER
-
58Good quality (B) · 58 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4080 SUPER
Quick answers
How much memory does Magistral Small 2507 need on the AMD Ryzen Embedded R2514 / R2544 NAS 64GB?
At Q8_0 it needs about 31.3 GB. The AMD Ryzen Embedded R2514 / R2544 NAS 64GB has 54.4 GB usable.
How fast is Magistral Small 2507 on the AMD Ryzen Embedded R2514 / R2544 NAS 64GB?
About 0.4 tok/s at Q8_0, an estimate from the hardware’s memory bandwidth and the size of the model.
Which quantization of Magistral Small 2507 should I use on the AMD Ryzen Embedded R2514 / R2544 NAS 64GB?
Q8_0. 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.