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Can the AMD Radeon RX 9060 XT 8GB run LLaVA 1.6 34B?

41 ptsPoor (D) · 41 of 100 points: Model quality 18.8/45, Memory fit 4.0/25, Speed 4.1/15, Memory use 15.0/15

Barely: most of the model spills into system RAM

Heavy offload. At Q4_K_M it needs about 23.2 GB of 8.0 GB usable, with an estimated speed of 3.0 tok/s.

Best quant
Q4_K_M
Generation speed
3.0 tok/s
Prompt processing
455 tok/s
First token (1K prompt)
2.3 s
Largest safe context
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Download LLaVA 1.6 34B

Recommended for the AMD Radeon RX 9060 XT 8GB: 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 llava:34b-v1.6-q4_K_M

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

Original weights · Hugging Face

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

huggingface.co/llava-hf/llava-v1.6-34b-hf (opens in a new tab)

No sign-in needed.

How the D 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.18.8 / 45
Memory fitFull marks when everything sits in GPU or unified memory; fewer when part spills to system RAM.4.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.4.1 / 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
Total41.9 / 10041 ptsPoor (D) · 41 of 100 points: Model quality 18.8/45, Memory fit 4.0/25, Speed 4.1/15, 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 9060 XT 8GB

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 15.9 GB 8.0 GB 5.7 tok/s Heavy offload 38 ptsPoor (D) · 38 of 100 points: Model quality 13.9/45, Memory fit 4.0/25, Speed 5.7/15, Memory use 15.0/15
Q3_K_M 19.0 GB 8.0 GB 4.2 tok/s Heavy offload 40 ptsPoor (D) · 40 of 100 points: Model quality 16.6/45, Memory fit 4.0/25, Speed 4.8/15, Memory use 15.0/15
Q4_K_M 23.2 GB 8.0 GB 3.0 tok/s Heavy offload 41 ptsPoor (D) · 41 of 100 points: Model quality 18.8/45, Memory fit 4.0/25, Speed 4.1/15, Memory use 15.0/15
Q5_K_M 26.7 GB 8.0 GB — Won't run 5 ptsWon't run (F) · 5 of 100 points: Model quality 5.8/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15
Q6_K 30.5 GB 8.0 GB — Won't run 5 ptsWon't run (F) · 5 of 100 points: Model quality 5.9/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15
Q8_0 38.8 GB 8.0 GB — Won't run 5 ptsWon't run (F) · 5 of 100 points: Model quality 5.9/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15
F16 71.5 GB 8.0 GB — Won't run 5 ptsWon't run (F) · 5 of 100 points: Model quality 5.9/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 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.