MASt3R_ViTLarge_BaseDecoder_512_catmlpdpt_metric
Will it run on your hardware?
Pick your GPU memory - see which quantizations fit, and the cheapest card for the rest
Need an exact figure for your context length? Use the VRAM calculator.
Run it locally
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Deep dive
Notes, sources, and the full write-up
MASt3R_ViTLarge_BaseDecoder_512_catmlpdpt_metric is an open-weight 3D generation model from naver, published on Hugging Face in July 2024. It has 690M parameters and is released under a custom license (see the model card).
HardwareLink to this section
At full FP16 precision the weights need about 1 GB of memory; 8-bit quantization brings that to roughly 1 GB. That is small enough for most consumer GPUs, Apple Silicon Macs, and many CPUs.
PopularityLink to this section
MASt3R_ViTLarge_BaseDecoder_512_catmlpdpt_metric had 74,925 downloads on Hugging Face in the last month and has 21 likes.
Run it locallyLink to this section
The weights are on Hugging Face and load with mast3r. Follow the model card for the exact setup and license terms.
Frequently asked
Quick answers to common questions
How much VRAM does MASt3R_ViTLarge_BaseDecoder_512_catmlpdpt_metric need?
MASt3R_ViTLarge_BaseDecoder_512_catmlpdpt_metric with 0.69B parameters needs approximately 1 GB at Q4_K_M quantization. Use our VRAM calculator for an exact estimate.
Is MASt3R_ViTLarge_BaseDecoder_512_catmlpdpt_metric better than other naver models?
MASt3R_ViTLarge_BaseDecoder_512_catmlpdpt_metric has 0.69B parameters with 8,192 context - a strong choice for 3d-generation.
What license is MASt3R_ViTLarge_BaseDecoder_512_catmlpdpt_metric under?
MASt3R_ViTLarge_BaseDecoder_512_catmlpdpt_metric is released under the Other license, making it suitable for most commercial and personal projects.
What hardware runs MASt3R_ViTLarge_BaseDecoder_512_catmlpdpt_metric well?
With 0.69B parameters, MASt3R_ViTLarge_BaseDecoder_512_catmlpdpt_metric requires adequate VRAM. High-end GPUs like the RTX 4090 (24GB), RTX 5090 (32GB), or Mac Studio with unified memory are good options. Check our hardware directory for specific recommendations.
What is the best quantization for MASt3R_ViTLarge_BaseDecoder_512_catmlpdpt_metric?
Q4_K_M is the recommended sweet spot - ~98% of FP16 quality at ~27% of the size. Q5_K_M (~1 GB) is an option if you have spare VRAM. Use our VRAM calculator to compare.
What models compete with MASt3R_ViTLarge_BaseDecoder_512_catmlpdpt_metric?
MASt3R_ViTLarge_BaseDecoder_512_catmlpdpt_metric competes with other models in its class. Browse our model directory for comparisons, benchmarks, and community reviews to find the best fit.
Nearby options
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