glpn-nyu
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
Copy-paste - running in under a minute
vllm serve vinvino02/glpn-nyuNew to this? Start with Ollama · serve to many users with vLLM.
Deep dive
Notes, sources, and the full write-up
glpn-nyu is an open-weight depth estimation model from vinvino02, published on Hugging Face in March 2022. It has 60M parameters and is released under the apache-2.0 license.
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
glpn-nyu had 5,602 downloads on Hugging Face in the last month and has 25 likes.
Run it locallyLink to this section
The weights are on Hugging Face and load with Hugging Face Transformers. Follow the model card for the exact setup and license terms.
Frequently asked
Quick answers to common questions
How much VRAM does glpn-nyu need?
glpn-nyu with 0.06B parameters needs approximately 1 GB at Q4_K_M quantization. Use our VRAM calculator for an exact estimate.
Is glpn-nyu better than other vinvino02 models?
glpn-nyu has 0.06B parameters with 8,192 context - a strong choice for depth-estimation.
What license is glpn-nyu under?
glpn-nyu is released under the apache-2.0 license, making it suitable for most commercial and personal projects.
What hardware runs glpn-nyu well?
With 0.06B parameters, glpn-nyu 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 glpn-nyu?
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 glpn-nyu?
glpn-nyu competes with other models in its class. Browse our model directory for comparisons, benchmarks, and community reviews to find the best fit.
Nearby options
Similar models and compatible hardware by spec