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Can the AMD Radeon RX 7900 XTX run AceReason Nemotron 14B?

84 ptsGreat (A) · 84 of 100 points: Model quality 29.4/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 14.9/15

Yes, it runs well

Runs well. At Q6_K it needs about 15.5 GB of 24.0 GB usable, with an estimated speed of 47.7 tok/s.

Best quant
Q6_K
Generation speed
47.7 tok/s
Prompt processing
5,155 tok/s
First token (1K prompt)
0.3 s
Largest safe context
50K

Download AceReason Nemotron 14B

Recommended for the AMD Radeon RX 7900 XTX: Q6_K. 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 Q6_K file (opens in a new tab)

huggingface.co/unsloth/AceReason-Nemotron-14B-GGUF (opens in a new tab)

ollama run hf.co/unsloth/AceReason-Nemotron-14B-GGUF:Q6_K

Original weights · Hugging Face

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

huggingface.co/nvidia/AceReason-Nemotron-14B (opens in a new tab)

No sign-in needed.

Links checked 1 week ago against Hugging Face, Ollama and GitHub.

How the A 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.29.4 / 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.15.0 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.14.9 / 15
Total84.3 / 10084 ptsGreat (A) · 84 of 100 points: Model quality 29.4/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 14.9/15

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

Every quantization on the AMD Radeon RX 7900 XTX

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 9.3 GB 24.0 GB 113 tok/s Runs well 69 ptsGood (B) · 69 of 100 points: Model quality 20.8/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 9.0/15 GGUF (opens in a new tab)
Q3_K_M 10.6 GB 24.0 GB 88.8 tok/s Runs well 75 ptsGreat (A) · 75 of 100 points: Model quality 24.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 10.2/15 GGUF (opens in a new tab)
Q4_K_M 12.4 GB 24.0 GB 68.7 tok/s Runs well 80 ptsGreat (A) · 80 of 100 points: Model quality 28.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 11.9/15 GGUF (opens in a new tab)
Q5_K_M 13.9 GB 24.0 GB 56.8 tok/s Runs well 82 ptsGreat (A) · 82 of 100 points: Model quality 28.8/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 13.4/15 GGUF (opens in a new tab)
Q6_K 15.5 GB 24.0 GB 47.7 tok/s Runs well 84 ptsGreat (A) · 84 of 100 points: Model quality 29.4/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 14.9/15 GGUF (opens in a new tab)
Q8_0 19.1 GB 24.0 GB 35.0 tok/s Runs well 83 ptsGreat (A) · 83 of 100 points: Model quality 29.7/45, Memory fit 25.0/25, Speed 14.0/15, Memory use 15.0/15 GGUF (UD-Q8_K_XL) (opens in a new tab)
F16 33.0 GB 24.0 GB 3.6 tok/s Heavy offload 53 ptsUsable (C) · 53 of 100 points: Model quality 29.7/45, Memory fit 4.0/25, Speed 4.5/15, Memory use 15.0/15 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.