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Can the AMD Radeon PRO W7900 run Laguna XS 2.1 (33B-A3B)?

91 ptsExcellent (S) · 91 of 100 points: Model quality 36.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15

Yes, it runs well

Runs well. At Q8_0 it needs about 39.8 GB of 48.0 GB usable, with an estimated speed of 77.5 tok/s.

Best quant
Q8_0
Generation speed
77.5 tok/s
Prompt processing
25,337 tok/s
First token (1K prompt)
0.3 s
Largest safe context
56K

Download Laguna XS 2.1 (33B-A3B)

Quantized files · GGUF

Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.

huggingface.co/poolside/Laguna-XS-2.1-GGUF (opens in a new tab)

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

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 S 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.36.9 / 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.15.0 / 15
Total91.9 / 10091 ptsExcellent (S) · 91 of 100 points: Model quality 36.9/45, Memory fit 25.0/25, Speed 15.0/15, 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 PRO W7900

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 17.7 GB 48.0 GB 250 tok/s Runs well 74 ptsGreat (A) · 74 of 100 points: Model quality 25.8/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 8.5/15 GGUF files (opens in a new tab)
Q3_K_M 20.7 GB 48.0 GB 197 tok/s Runs well 80 ptsGreat (A) · 80 of 100 points: Model quality 31.0/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 10.0/15 GGUF files (opens in a new tab)
Q4_K_M 24.7 GB 48.0 GB 152 tok/s Runs well 86 ptsExcellent (S) · 86 of 100 points: Model quality 35.1/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 11.9/15 GGUF (opens in a new tab)
Q5_K_M 28.1 GB 48.0 GB 126 tok/s Runs well 89 ptsExcellent (S) · 89 of 100 points: Model quality 35.8/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 13.5/15 GGUF files (opens in a new tab)
Q6_K 31.8 GB 48.0 GB 106 tok/s Runs well 91 ptsExcellent (S) · 91 of 100 points: Model quality 36.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF files (opens in a new tab)
Q8_0 39.8 GB 48.0 GB 77.5 tok/s Runs well 91 ptsExcellent (S) · 91 of 100 points: Model quality 36.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF files (opens in a new tab)
F16 71.2 GB 48.0 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.