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Can the AMD Ryzen Embedded V1500B NAS (32 GB) run K2 Horizon 7B?

56Good quality (B) · 56 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 61/100 (quality, fit, speed and memory use) sets the ranking.

Yes, but slowly

Slow. At Q2_K it needs about 7.5 GB of 26.2 GB usable, with an estimated speed of 3.6 tok/s.

Best quant
Q2_K
Generation speed
3.6 tok/s
Prompt processing
10.0 tok/s
First token (1K prompt)
102.4 s
Largest safe context
132K

Best app to run it on the AMD Ryzen Embedded V1500B NAS (32 GB)

On Linux

llama.cpp

Command line + local API · runs on llama.cpp

  • Usually the first to support new model architectures.
llama-server -hf IFM/K2-Horizon-7B-GGUF:Q2_K

Want an agent? K2 Horizon 7B supports tool use, so you can pair a llama.cpp or MLX LM server with one of these. Apps that run on this computer come first.

Coding agents

Personal assistants

How we choose: the files published for this model, which apps run in a container on a NAS without a graphics card (models run on its processor), and whether the model fits fully in the memory models can use. Details.

Download K2 Horizon 7B

Quantized files · GGUF

Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.

huggingface.co/IFM/K2-Horizon-7B-GGUF (opens in a new tab)

ollama run hf.co/IFM/K2-Horizon-7B-GGUF

Original weights · Hugging Face

Full-precision files from Institute of Foundation Models, for fine-tuning, vLLM, Transformers.

huggingface.co/IFM/K2-Horizon-7B (opens in a new tab)

No sign-in needed.

Official repo · GitHub

Reference code, inference scripts and docs from Institute of Foundation Models. The weights themselves download from Hugging Face.

github.com/ifm-ai/xllm (opens in a new tab)

IFM’s official training code (xLLM) for the K2 Horizon family.

git clone https://github.com/ifm-ai/xllm

Links checked 3 days ago against Hugging Face, Ollama and GitHub.

How it’s rated

Quality 56Good quality (B) · 56 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 61/100 (quality, fit, speed and memory use) sets the ranking.
How capable the model itself is at Q2_K, from its editorial quality tier scaled by the quantization or precision. It’s the same on any hardware that runs this variant. Scale: A+ 85+ · A 70+ · B 55+ · C 40+ · D under 40.
Runs Slow
How well it runs on the AMD Ryzen Embedded V1500B NAS (32 GB): speed, capped by how well it fits in memory. Runs great: 30+ tokens/s (or near the image, video or decision speed target) · Runs well: 10+ tokens/s · Slow: 3+ tokens/s · Very slow: under 3 · Won’t run: doesn’t fit even with offload. A tight fit or RAM offload caps it at Runs well; heavy offload caps it at Slow.

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 qualityEditorial quality tier of the model, scaled by the quantization or precision used.25.2 / 45
Memory fitFull marks when the model fits in the share of the NAS’s memory that models can use (the rest stays with the NAS system and its storage services); fewer when it goes past that limit.25.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.4.5 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.6.6 / 15
Match score61.3 / 100

The match score orders results; it is not shown as a grade. Quality and Runs are the two ratings in the tables.

Every quantization on the AMD Ryzen Embedded V1500B NAS (32 GB)

Quant Memory needed Available Speed Runs Quality Download
Q2_K 7.5 GB 26.2 GB 3.6 tok/s Slow 56Good quality (B) · 56 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 61/100 (quality, fit, speed and memory use) sets the ranking. GGUF files (opens in a new tab)
Q3_K_M 8.3 GB 26.2 GB 2.8 tok/s Very slow 67Good quality (B) · 67 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 66/100 (quality, fit, speed and memory use) sets the ranking. GGUF files (opens in a new tab)
Q4_K_M 9.4 GB 26.2 GB 2.2 tok/s Very slow 76Great quality (A) · 76 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 70/100 (quality, fit, speed and memory use) sets the ranking. GGUF (opens in a new tab)
Q5_K_M 10.3 GB 26.2 GB 1.8 tok/s Very slow 77Great quality (A) · 77 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 72/100 (quality, fit, speed and memory use) sets the ranking. GGUF (opens in a new tab)
Q6_K 11.3 GB 26.2 GB 1.5 tok/s Very slow 79Great quality (A) · 79 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 73/100 (quality, fit, speed and memory use) sets the ranking. GGUF (opens in a new tab)
Q8_0 13.4 GB 26.2 GB 1.1 tok/s Very slow 80Great quality (A) · 80 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 75/100 (quality, fit, speed and memory use) sets the ranking. GGUF (opens in a new tab)
F16 21.9 GB 26.2 GB 0.5 tok/s Very slow 80Great quality (A) · 80 of 100: how capable the model is at F16, whatever it runs on. Match score 77/100 (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

Quick answers

How much memory does K2 Horizon 7B need on the AMD Ryzen Embedded V1500B NAS 32GB?

At Q2_K it needs about 7.5 GB. The AMD Ryzen Embedded V1500B NAS 32GB has 26.2 GB usable.

How fast is K2 Horizon 7B on the AMD Ryzen Embedded V1500B NAS 32GB?

About 3.6 tok/s at Q2_K, an estimate from the hardware’s memory bandwidth and the size of the model.

Which quantization of K2 Horizon 7B should I use on the AMD Ryzen Embedded V1500B NAS 32GB?

Q2_K. 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.

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