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Can the AMD Ryzen AI Max 390 (64 GB) run Hunyuan 1.8B Instruct?

22Basic quality (D) · 22 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.

Yes, it runs great

Runs great. At Q8_0 it needs about 6.9 GB of 48.0 GB usable, with an estimated speed of 77.0 tok/s.

Best quant
Q8_0
Generation speed
77.0 tok/s
Prompt processing
15,898 tok/s
First token (1K prompt)
0.3 s
Largest safe context
256K

Best app to run it on the AMD Ryzen AI Max 390 (64 GB)

On Windows

Lemonade

Desktop app · runs on llama.cpp, ONNX Runtime GenAI (Ryzen AI NPU)

  • Built for Ryzen AI and Strix Halo, including NPU + iGPU modes on Windows.
lemonade pull bartowski/tencent_Hunyuan-1.8B-Instruct-GGUF:Q8_0
  • LM Studio Point-and-click: search, download and chat in one window.
  • llama.cpp Usually the first to support new model architectures.

On Linux

Lemonade

Desktop app · runs on llama.cpp, ONNX Runtime GenAI (Ryzen AI NPU)

  • Built for Ryzen AI and Strix Halo, including NPU + iGPU modes on Windows.
lemonade pull bartowski/tencent_Hunyuan-1.8B-Instruct-GGUF:Q8_0
  • LM Studio Point-and-click: search, download and chat in one window.
  • llama.cpp Usually the first to support new model architectures.

How we choose: the files published for this model, your operating system and GPU, whether it fits fully in memory, and published speed tests (MLX vs llama.cpp on Apple silicon, vLLM vs llama.cpp vs Ollama on NVIDIA). Details.

Download Hunyuan 1.8B Instruct

Recommended for the AMD Ryzen AI Max 390 (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/bartowski/tencent_Hunyuan-1.8B-Instruct-GGUF (opens in a new tab)

ollama run hf.co/bartowski/tencent_Hunyuan-1.8B-Instruct-GGUF:Q8_0

Original weights · Hugging Face

Full-precision files from Tencent, for fine-tuning, vLLM, Transformers.

huggingface.co/tencent/Hunyuan-1.8B-Instruct (opens in a new tab)

No sign-in needed.

Official repo · GitHub

Reference code, inference scripts and docs from Tencent. The weights themselves download from Hugging Face.

github.com/Tencent-Hunyuan/Hunyuan-7B (opens in a new tab)

git clone https://github.com/Tencent-Hunyuan/Hunyuan-7B

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

How it’s rated

Quality 22Basic quality (D) · 22 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.
How capable the model itself is at Q8_0, 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 Runs great
How well it runs on the AMD Ryzen AI Max 390 (64 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.9.9 / 45
Memory fitFull marks when the model fits in the share of unified memory the GPU can use; 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.15.0 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.3.3 / 15
Match score53.2 / 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 AI Max 390 (64 GB)

Quant Memory needed Available Speed Runs Quality Download
Q2_K 5.7 GB 48.0 GB 248 tok/s Runs great 15Basic quality (D) · 15 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 49/100 (quality, fit, speed and memory use) sets the ranking. GGUF (opens in a new tab)
Q3_K_M 5.9 GB 48.0 GB 195 tok/s Runs great 18Basic quality (D) · 18 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 51/100 (quality, fit, speed and memory use) sets the ranking. GGUF (opens in a new tab)
Q4_K_M 6.1 GB 48.0 GB 151 tok/s Runs great 20Basic quality (D) · 20 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 6.2 GB 48.0 GB 125 tok/s Runs great 21Basic quality (D) · 21 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 6.4 GB 48.0 GB 105 tok/s Runs great 21Basic quality (D) · 21 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 52/100 (quality, fit, speed and memory use) sets the ranking. GGUF (opens in a new tab)
Q8_0 6.9 GB 48.0 GB 77.0 tok/s Runs great 22Basic quality (D) · 22 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. GGUF (opens in a new tab)
F16 8.6 GB 48.0 GB 35.5 tok/s Runs great 22Basic quality (D) · 22 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. 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 Hunyuan 1.8B Instruct need on the AMD Ryzen AI Max 390 64GB?

At Q8_0 it needs about 6.9 GB. The AMD Ryzen AI Max 390 64GB has 48.0 GB usable.

How fast is Hunyuan 1.8B Instruct on the AMD Ryzen AI Max 390 64GB?

About 77.0 tok/s at Q8_0, an estimate from the hardware’s memory bandwidth and the size of the model.

Which quantization of Hunyuan 1.8B Instruct should I use on the AMD Ryzen AI Max 390 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.

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