Pi3
yyfz233bsd-2-clausevision

Pi3

Updated Nov 13, 2026
Parameters
0.96B
Context
8,192
License
bsd-2-clause
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 Pi3 with real runtime overhead.
Q4_K_M
1 GB
Q5_K_M
1 GB
Q8_0
1 GB
FP16
2 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 yyfz233/Pi3

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

Deep dive

Notes, sources, and the full write-up

Pi3 is an open-weight 3D generation model from yyfz233, published on Hugging Face in July 2025. It has 960M parameters and is released under the bsd-2-clause license.

HardwareLink to this section

At full FP16 precision the weights need about 2 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

Pi3 had 56,512 downloads on Hugging Face in the last month and has 22 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 Pi3 need?

Pi3 with 0.96B parameters needs approximately 1 GB at Q4_K_M quantization. Use our VRAM calculator for an exact estimate.

Is Pi3 better than other yyfz233 models?

Pi3 has 0.96B parameters with 8,192 context - a strong choice for 3d-generation.

What license is Pi3 under?

Pi3 is released under the bsd-2-clause license, making it suitable for most commercial and personal projects.

What hardware runs Pi3 well?

With 0.96B parameters, Pi3 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 Pi3?

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 Pi3?

Pi3 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