Beam 1.0 (501B-A23B) on AMD Ryzen Embedded V1780B NAS (16 GB)
Can the AMD Ryzen Embedded V1780B NAS (16 GB) run Beam 1.0 (501B-A23B)?
No, it doesn’t fit
No. Beam 1.0 (501B-A23B) needs about 202 GB even at Q2_K; the AMD Ryzen Embedded V1780B NAS (16 GB) has 12.0 GB usable.
Download Beam 1.0 (501B-A23B)
Recommended: Q2_K. Every other quantization has its own download link in the table below.
Ollama
Ollama offers this only as a cloud model (it runs on Ollama’s servers, not your machine). To run it locally, use the GGUF files below.
Quantized files · GGUF
Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.
Download the Q2_K (UD-Q2_K_XL) files (opens in a new tab)
huggingface.co/unsloth/Beam-1.0-501B-A23B-GGUF (opens in a new tab)
ollama run hf.co/unsloth/Beam-1.0-501B-A23B-GGUFOriginal weights · Hugging Face
Full-precision files from Reflection AI, for fine-tuning, vLLM, Transformers.
huggingface.co/reflection/Beam-1.0-501B-A23B (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 | 8.9 / 45 | |
|---|---|---|
| Memory fit | 0.0 / 25 | |
| Speed | 0.0 / 15 | |
| Memory use | 0.0 / 15 | |
| Match score | 8.9 / 100 |
Every quantization on the AMD Ryzen Embedded V1780B NAS (16 GB)
| Quant | Memory needed | Available | Speed | Runs | Quality | Download |
|---|---|---|---|---|---|---|
Q2_K | 202 GB | 12.0 GB | — | Won't run | 66Good quality (B) · 66 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 8/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (UD-Q2_K_XL) · folder (opens in a new tab) |
Q3_K_M | 247 GB | 12.0 GB | — | Won't run | 79Great quality (A) · 79 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 10/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (UD-Q3_K_XL) · folder (opens in a new tab) |
Q4_K_M | 308 GB | 12.0 GB | — | Won't run | 89Excellent quality (A+) · 89 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 12/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (UD-Q4_K_XL) · folder (opens in a new tab) |
Q5_K_M | 358 GB | 12.0 GB | — | Won't run | 91Excellent quality (A+) · 91 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 12/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (UD-Q5_K_XL) · folder (opens in a new tab) |
Q6_K | 413 GB | 12.0 GB | — | Won't run | 93Excellent quality (A+) · 93 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 12/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (UD-Q6_K_XL) · folder (opens in a new tab) |
Q8_0 | 533 GB | 12.0 GB | — | Won't run | 94Excellent quality (A+) · 94 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 12/100 (quality, fit, speed and memory use) sets the ranking. | GGUF · folder (opens in a new tab) |
F16 | 1,004 GB | 12.0 GB | — | Won't run | 94Excellent quality (A+) · 94 of 100: how capable the model is at F16, whatever it runs on. Match score 12/100 (quality, fit, speed and memory use) sets the ranking. | GGUF · folder (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
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89Excellent quality (A+) · 89 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 92/100 (quality, fit, speed and memory use) sets the ranking.
Apple M3 Ultra (512 GB)
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89Excellent quality (A+) · 89 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 94/100 (quality, fit, speed and memory use) sets the ranking.
Apple M5 Ultra (512 GB)
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79Great quality (A) · 79 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking.
AMD Instinct MI350X
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66Good quality (B) · 66 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 84/100 (quality, fit, speed and memory use) sets the ranking.
AMD Instinct MI325X
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66Good quality (B) · 66 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 84/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GB300 Grace Blackwell Ultra Desktop Superchip
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66Good quality (B) · 66 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 69/100 (quality, fit, speed and memory use) sets the ranking.
AMD Instinct MI300X
Models that do run on the AMD Ryzen Embedded V1780B NAS (16 GB)
- 58Good quality (B) · 58 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 75/100 (quality, fit, speed and memory use) sets the ranking. Maple Preview (20B-A1B)
- 69Good quality (B) · 69 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 75/100 (quality, fit, speed and memory use) sets the ranking. Nemotron 3.5 Bolt E4B
- 67Good quality (B) · 67 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 74/100 (quality, fit, speed and memory use) sets the ranking. Gemma 4 E4B
- 58Good quality (B) · 58 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 74/100 (quality, fit, speed and memory use) sets the ranking. Mellum2.1 Thinking (12B-A2.5B)
- 67Good quality (B) · 67 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 73/100 (quality, fit, speed and memory use) sets the ranking. K2 Horizon 7B
Quick answers
How much memory does Beam 1.0 (501B-A23B) need on the AMD Ryzen Embedded V1780B NAS 16GB?
Even at Q2_K it needs about 202 GB; the AMD Ryzen Embedded V1780B NAS 16GB has 12.0 GB usable.
What can the AMD Ryzen Embedded V1780B NAS 16GB run instead?
Maple Preview (20B-A1B), Nemotron 3.5 Bolt E4B and Gemma 4 E4B run best on it; the page lists more, each with its speed.
What hardware can run Beam 1.0 (501B-A23B)?
M3 Ultra 512GB, M5 Ultra 512GB and AMD Instinct MI350X 288GB 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.