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Can the AMD Radeon RX 9060 XT 8GB run Laguna XS 2.1 (33B-A3B)?

63 ptsGood (B) · 63 of 100 points: Model quality 35.1/45, Memory fit 4.0/25, Speed 9.9/15, Memory use 15.0/15

Barely: most of the model spills into system RAM

Heavy offload. At Q4_K_M it needs about 22.7 GB of 8.0 GB usable, with an estimated speed of 17.3 tok/s.

Best quant
Q4_K_M
Generation speed
17.3 tok/s
Prompt processing
5,229 tok/s
First token (1K prompt)
0.3 s
Largest safe context
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Download Laguna XS 2.1 (33B-A3B)

Recommended for the AMD Radeon RX 9060 XT 8GB: 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/poolside/Laguna-XS-2.1-GGUF (opens in a new tab)

ollama run hf.co/poolside/Laguna-XS-2.1-GGUF:Q4_K_M

Original weights · Hugging Face

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

huggingface.co/poolside/Laguna-XS-2.1 (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.35.1 / 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.9.9 / 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
Total63.9 / 10063 ptsGood (B) · 63 of 100 points: Model quality 35.1/45, Memory fit 4.0/25, Speed 9.9/15, 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 15.7 GB 8.0 GB 33.0 tok/s Heavy offload 58 ptsGood (B) · 58 of 100 points: Model quality 25.8/45, Memory fit 4.0/25, Speed 13.6/15, Memory use 15.0/15 GGUF files (opens in a new tab)
Q3_K_M 18.7 GB 8.0 GB 23.9 tok/s Heavy offload 61 ptsGood (B) · 61 of 100 points: Model quality 31.0/45, Memory fit 4.0/25, Speed 11.6/15, Memory use 15.0/15 GGUF files (opens in a new tab)
Q4_K_M 22.7 GB 8.0 GB 17.3 tok/s Heavy offload 63 ptsGood (B) · 63 of 100 points: Model quality 35.1/45, Memory fit 4.0/25, Speed 9.9/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q5_K_M 26.1 GB 8.0 GB — Won't run 10 ptsWon't run (F) · 10 of 100 points: Model quality 10.7/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF files (opens in a new tab)
Q6_K 29.8 GB 8.0 GB — Won't run 10 ptsWon't run (F) · 10 of 100 points: Model quality 11.0/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF files (opens in a new tab)
Q8_0 37.8 GB 8.0 GB — Won't run 11 ptsWon't run (F) · 11 of 100 points: Model quality 11.1/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF files (opens in a new tab)
F16 69.2 GB 8.0 GB — Won't run 11 ptsWon't run (F) · 11 of 100 points: Model quality 11.1/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 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.