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Can the AMD Ryzen AI 9 HX 470 (DDR5 SO-DIMM) (32 GB) run Jamba2 3B?

60 ptsGood (B) · 60 of 100 points: Model quality 18.0/45, Memory fit 25.0/25, Speed 13.3/15, Memory use 4.2/15

Yes, it runs well

Runs well. At Q4_K_M it needs about 4.4 GB of 24.0 GB usable, with an estimated speed of 31.3 tok/s.

Best quant
Q4_K_M
Generation speed
31.3 tok/s
Prompt processing
5,197 tok/s
First token (1K prompt)
0.3 s
Largest safe context
256K

Download Jamba2 3B

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.

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/bartowski/ai21labs_AI21-Jamba2-3B-GGUF (opens in a new tab)

ollama run hf.co/bartowski/ai21labs_AI21-Jamba2-3B-GGUF:Q4_K_M

Original weights · Hugging Face

Full-precision files from AI21 Labs, for fine-tuning, vLLM, Transformers.

huggingface.co/ai21labs/AI21-Jamba2-3B (opens in a new tab)

No sign-in needed.

How the B 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.18.0 / 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.13.3 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.4.2 / 15
Total60.4 / 10060 ptsGood (B) · 60 of 100 points: Model quality 18.0/45, Memory fit 25.0/25, Speed 13.3/15, Memory use 4.2/15

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 3.7 GB 24.0 GB 51.3 tok/s Runs well 56 ptsUsable (C) · 56 of 100 points: Model quality 13.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 3.6/15 GGUF (opens in a new tab)
Q3_K_M 4.0 GB 24.0 GB 40.4 tok/s Runs well 59 ptsGood (B) · 59 of 100 points: Model quality 15.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 3.9/15 GGUF (opens in a new tab)
Q4_K_M 4.4 GB 24.0 GB 31.3 tok/s Runs well 60 ptsGood (B) · 60 of 100 points: Model quality 18.0/45, Memory fit 25.0/25, Speed 13.3/15, Memory use 4.2/15 GGUF (opens in a new tab)
Q5_K_M 4.7 GB 24.0 GB 25.8 tok/s Runs well 59 ptsGood (B) · 59 of 100 points: Model quality 18.3/45, Memory fit 25.0/25, Speed 12.1/15, Memory use 4.5/15 GGUF (opens in a new tab)
Q6_K 5.0 GB 24.0 GB 21.7 tok/s Runs well 59 ptsGood (B) · 59 of 100 points: Model quality 18.7/45, Memory fit 25.0/25, Speed 11.0/15, Memory use 4.8/15 GGUF (opens in a new tab)
Q8_0 5.7 GB 24.0 GB 15.9 tok/s Runs well 58 ptsGood (B) · 58 of 100 points: Model quality 18.9/45, Memory fit 25.0/25, Speed 9.5/15, Memory use 5.5/15 GGUF (opens in a new tab)
F16 8.6 GB 24.0 GB 7.3 tok/s Runs well 58 ptsGood (B) · 58 of 100 points: Model quality 18.9/45, Memory fit 25.0/25, Speed 6.4/15, Memory use 8.3/15 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

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.