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Can the NVIDIA GeForce RTX 4080 SUPER run Mage-VL 4.7B?

80 ptsGreat (A) · 80 of 100 points: Model quality 25.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15

Yes, it runs well

Runs well. At F16 it needs about 12.1 GB of 16.0 GB usable, with an estimated speed of 44.7 tok/s.

Best quant
F16
Generation speed
44.7 tok/s
Prompt processing
7,929 tok/s
First token (1K prompt)
0.3 s
Largest safe context
33K

Download Mage-VL 4.7B

Original weights · Hugging Face

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

huggingface.co/microsoft/Mage-VL (opens in a new tab)

No sign-in needed.

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

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.25.2 / 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
Total80.2 / 10080 ptsGreat (A) · 80 of 100 points: Model quality 25.2/45, 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 NVIDIA GeForce RTX 4080 SUPER

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 4.5 GB 16.0 GB 313 tok/s Runs well 64 ptsGood (B) · 64 of 100 points: Model quality 17.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 6.5/15 All files (opens in a new tab)
Q3_K_M 4.9 GB 16.0 GB 246 tok/s Runs well 68 ptsGood (B) · 68 of 100 points: Model quality 21.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 7.1/15 All files (opens in a new tab)
Q4_K_M 5.5 GB 16.0 GB 191 tok/s Runs well 71 ptsGood (B) · 71 of 100 points: Model quality 23.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 7.9/15 All files (opens in a new tab)
Q5_K_M 6.0 GB 16.0 GB 157 tok/s Runs well 73 ptsGreat (A) · 73 of 100 points: Model quality 24.4/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 8.6/15 All files (opens in a new tab)
Q6_K 6.5 GB 16.0 GB 132 tok/s Runs well 74 ptsGreat (A) · 74 of 100 points: Model quality 24.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 9.4/15 All files (opens in a new tab)
Q8_0 7.6 GB 16.0 GB 97.0 tok/s Runs well 76 ptsGreat (A) · 76 of 100 points: Model quality 25.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 11.0/15 All files (opens in a new tab)
F16 12.1 GB 16.0 GB 44.7 tok/s Runs well 80 ptsGreat (A) · 80 of 100 points: Model quality 25.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 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.