reloc3r-512
siyan824Othervision

reloc3r-512

Updated Nov 13, 2026
Parameters
0.43B
Context
8,192
License
Other
Updated
Nov 13, 2026

Will it run on your hardware?

Pick your GPU memory - see which quantizations fit, and the cheapest card for the rest

Runs on your 24 GB - best at FP16
4 of 4 quantizations fit reloc3r-512 with real runtime overhead.
Q4_K_M
1 GB
Q5_K_M
1 GB
Q8_0
1 GB
FP16
1 GB
fits tight too big

Need an exact figure for your context length? Use the VRAM calculator.

Run it locally

Copy-paste - running in under a minute

vLLMOpenAI-compatible API
vllm serve siyan824/reloc3r-512

New to this? Start with Ollama · serve to many users with vLLM.

Deep dive

Notes, sources, and the full write-up

reloc3r-512 is an open-weight 3D generation model from siyan824, published on Hugging Face in January 2025. It has 430M 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

reloc3r-512 had 93,355 downloads on Hugging Face in the last month and has 7 likes.

Run it locallyLink to this section

The weights are on Hugging Face and load with PyTorch. Follow the model card for the exact setup and license terms.

Frequently asked

Quick answers to common questions

How much VRAM does reloc3r-512 need?

reloc3r-512 with 0.43B parameters needs approximately 1 GB at Q4_K_M quantization. Use our VRAM calculator for an exact estimate.

Is reloc3r-512 better than other siyan824 models?

reloc3r-512 has 0.43B parameters with 8,192 context - a strong choice for 3d-generation.

What license is reloc3r-512 under?

reloc3r-512 is released under the Other license, making it suitable for most commercial and personal projects.

What hardware runs reloc3r-512 well?

With 0.43B parameters, reloc3r-512 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 reloc3r-512?

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 reloc3r-512?

reloc3r-512 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