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Can the AMD Radeon RX 7900 XTX run Granite 4.1 30B?

83 ptsGreat (A) · 83 of 100 points: Model quality 30.8/45, Memory fit 24.0/25, Speed 14.1/15, Memory use 15.0/15

Yes, with little memory to spare

Tight fit. At Q4_K_M it needs about 21.6 GB of 24.0 GB usable, with an estimated speed of 35.1 tok/s.

Best quant
Q4_K_M
Generation speed
35.1 tok/s
Prompt processing
2,637 tok/s
First token (1K prompt)
0.4 s
Largest safe context
17K

Download Granite 4.1 30B

Recommended for the AMD Radeon RX 7900 XTX: 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 granite4.1:30b-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/ibm-granite/granite-4.1-30b-GGUF (opens in a new tab)

ollama run hf.co/ibm-granite/granite-4.1-30b-GGUF:Q4_K_M

Original weights · Hugging Face

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

huggingface.co/ibm-granite/granite-4.1-30b (opens in a new tab)

No sign-in needed.

Official repo · GitHub

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

github.com/ibm-granite/granite-4.1-language-models (opens in a new tab)

git clone https://github.com/ibm-granite/granite-4.1-language-models

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.30.8 / 45
Memory fitFull marks when everything sits in GPU or unified memory; fewer when part spills to system RAM.24.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.14.1 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.15.0 / 15
Total83.8 / 10083 ptsGreat (A) · 83 of 100 points: Model quality 30.8/45, Memory fit 24.0/25, Speed 14.1/15, Memory use 15.0/15

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 15.5 GB 24.0 GB 57.7 tok/s Runs well 77 ptsGreat (A) · 77 of 100 points: Model quality 22.7/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 14.9/15 GGUF (opens in a new tab)
Q3_K_M 18.1 GB 24.0 GB 45.4 tok/s Runs well 82 ptsGreat (A) · 82 of 100 points: Model quality 27.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q4_K_M 21.6 GB 24.0 GB 35.1 tok/s Tight fit 83 ptsGreat (A) · 83 of 100 points: Model quality 30.8/45, Memory fit 24.0/25, Speed 14.1/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q5_K_M 24.4 GB 24.0 GB 23.3 tok/s Runs with offload 67 ptsGood (B) · 67 of 100 points: Model quality 31.4/45, Memory fit 10.0/25, Speed 11.4/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q6_K 27.6 GB 24.0 GB 8.9 tok/s Runs with offload 64 ptsGood (B) · 64 of 100 points: Model quality 32.1/45, Memory fit 10.0/25, Speed 7.1/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q8_0 34.5 GB 24.0 GB 3.6 tok/s Heavy offload 55 ptsUsable (C) · 55 of 100 points: Model quality 32.4/45, Memory fit 4.0/25, Speed 4.5/15, Memory use 15.0/15 GGUF (opens in a new tab)
F16 61.7 GB 24.0 GB — Won't run 9 ptsWon't run (F) · 9 of 100 points: Model quality 9.7/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF · part 1 of 5 (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.