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Can the AMD Radeon RX 7900 XTX run StableLM 2 12B Chat?

67 ptsGood (B) · 67 of 100 points: Model quality 12.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 14.9/15

Yes, it runs well

Runs well. At Q8_0 it needs about 15.5 GB of 24.0 GB usable, with an estimated speed of 42.6 tok/s.

Best quant
Q8_0
Generation speed
42.6 tok/s
Prompt processing
6,271 tok/s
First token (1K prompt)
0.3 s
Largest safe context
4K

Download StableLM 2 12B Chat

Recommended for the AMD Radeon RX 7900 XTX: Q8_0. 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 stablelm2:12b-chat-q8_0

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 Q8_0 file (opens in a new tab)

huggingface.co/stabilityai/stablelm-2-12b-chat-GGUF (opens in a new tab)

ollama run hf.co/stabilityai/stablelm-2-12b-chat-GGUF:Q8_0

Original weights · Hugging Face

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

huggingface.co/stabilityai/stablelm-2-12b-chat (opens in a new tab)

No sign-in needed.

Links checked 7 days ago against Hugging Face, Ollama and GitHub.

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.12.6 / 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
Total67.5 / 10067 ptsGood (B) · 67 of 100 points: Model quality 12.6/45, 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 7.5 GB 24.0 GB 137 tok/s Runs well 56 ptsUsable (C) · 56 of 100 points: Model quality 8.8/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 7.2/15 GGUF (opens in a new tab)
Q3_K_M 8.6 GB 24.0 GB 108 tok/s Runs well 58 ptsGood (B) · 58 of 100 points: Model quality 10.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 8.3/15 GGUF (opens in a new tab)
Q4_K_M 10.0 GB 24.0 GB 83.6 tok/s Runs well 61 ptsGood (B) · 61 of 100 points: Model quality 12.0/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 9.7/15 GGUF (opens in a new tab)
Q5_K_M 11.3 GB 24.0 GB 69.1 tok/s Runs well 63 ptsGood (B) · 63 of 100 points: Model quality 12.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 10.8/15 GGUF (opens in a new tab)
Q6_K 12.6 GB 24.0 GB 58.0 tok/s Runs well 64 ptsGood (B) · 64 of 100 points: Model quality 12.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 12.1/15 GGUF (opens in a new tab)
Q8_0 15.5 GB 24.0 GB 42.6 tok/s Runs well 67 ptsGood (B) · 67 of 100 points: Model quality 12.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 14.9/15 GGUF (opens in a new tab)
F16 26.9 GB 24.0 GB 8.3 tok/s Runs with offload 44 ptsUsable (C) · 44 of 100 points: Model quality 12.6/45, Memory fit 10.0/25, Speed 6.8/15, Memory use 15.0/15 GGUF (opens in a new tab) Original weights (opens in a new tab)

Memory figures assume 4K 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.