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Can the AMD Ryzen AI 9 HX 470 (DDR5 SO-DIMM) (32 GB) run Gemma 2 2B?

55 ptsUsable (C) · 55 of 100 points: Model quality 12.0/45, Memory fit 25.0/25, Speed 14.3/15, Memory use 4.4/15

Yes, it runs well

Runs well. At Q4_K_M it needs about 4.6 GB of 24.0 GB usable, with an estimated speed of 36.3 tok/s.

Best quant
Q4_K_M
Generation speed
36.3 tok/s
Prompt processing
6,034 tok/s
First token (1K prompt)
0.3 s
Largest safe context
8K

Download Gemma 2 2B

Recommended for the AMD Ryzen AI 9 HX 470 (DDR5 SO-DIMM) (32 GB): Q4_K_M. Every other quantization has its own download link in the table below.

Quickest · Ollama

One command downloads a ready-to-run version and starts a chat.

ollama run gemma2:2b-instruct-q4_K_M

Get Ollama at ollama.com/download (opens in a new tab) · model page (opens in a new tab)

Quantized files · GGUF

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

Download the Q4_K_M file (opens in a new tab)

huggingface.co/lmstudio-community/gemma-2-2b-it-GGUF (opens in a new tab)

ollama run hf.co/lmstudio-community/gemma-2-2b-it-GGUF:Q4_K_M

Original weights · Hugging Face

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

huggingface.co/google/gemma-2-2b-it (opens in a new tab)

Free Hugging Face account needed: request access on the model page, and Google approves it (usually within minutes to a few hours).

Official repo · GitHub

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

github.com/google-deepmind/gemma (opens in a new tab)

git clone https://github.com/google-deepmind/gemma

Google DeepMind’s official Gemma library.

Links checked 6 days ago against Hugging Face, Ollama and GitHub.

How the C grade is scored

Every result gets up to 100 points from four parts. The points decide the letter grade.

Model qualityEditorial quality tier of the model, scaled by the quantization or precision used.12.0 / 45
Memory fitFull marks when everything sits in GPU or unified memory; fewer when part spills to system RAM.25.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.14.3 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.4.4 / 15
Total55.7 / 10055 ptsUsable (C) · 55 of 100 points: Model quality 12.0/45, Memory fit 25.0/25, Speed 14.3/15, Memory use 4.4/15

Grade scale: S 85+ · A 72+ · B 58+ · C 42+ · D 25+ · F under 25 points.

Every quantization on the AMD Ryzen AI 9 HX 470 (DDR5 SO-DIMM) (32 GB)

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 4.1 GB 24.0 GB 59.6 tok/s Runs well 52 ptsUsable (C) · 52 of 100 points: Model quality 8.8/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 3.9/15
Q3_K_M 4.3 GB 24.0 GB 46.9 tok/s Runs well 54 ptsUsable (C) · 54 of 100 points: Model quality 10.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 4.1/15 GGUF (Q3_K_L) (opens in a new tab)
Q4_K_M 4.6 GB 24.0 GB 36.3 tok/s Runs well 55 ptsUsable (C) · 55 of 100 points: Model quality 12.0/45, Memory fit 25.0/25, Speed 14.3/15, Memory use 4.4/15 GGUF (opens in a new tab)
Q5_K_M 4.9 GB 24.0 GB 30.0 tok/s Runs well 54 ptsUsable (C) · 54 of 100 points: Model quality 12.2/45, Memory fit 25.0/25, Speed 13.0/15, Memory use 4.7/15 GGUF (opens in a new tab)
Q6_K 5.2 GB 24.0 GB 25.2 tok/s Runs well 54 ptsUsable (C) · 54 of 100 points: Model quality 12.5/45, Memory fit 25.0/25, Speed 11.9/15, Memory use 5.0/15 GGUF (opens in a new tab)
Q8_0 5.8 GB 24.0 GB 18.5 tok/s Runs well 53 ptsUsable (C) · 53 of 100 points: Model quality 12.6/45, Memory fit 25.0/25, Speed 10.2/15, Memory use 5.6/15 GGUF (opens in a new tab)
F16 8.2 GB 24.0 GB 8.5 tok/s Runs well 52 ptsUsable (C) · 52 of 100 points: Model quality 12.6/45, Memory fit 25.0/25, Speed 6.9/15, Memory use 7.9/15 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

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.