Confucius4-R2T2
netease-youdaoOtheraudio

Confucius4-R2T2

Updated Nov 13, 2026
Parameters
2B
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 Confucius4-R2T2 with real runtime overhead.
Q4_K_M
1 GB
Q5_K_M
1 GB
Q8_0
2 GB
FP16
4 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 netease-youdao/Confucius4-R2T2

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

Deep dive

Notes, sources, and the full write-up

Confucius4-R2T2 is an open-weight speech recognition model from netease-youdao, published on Hugging Face in September 2026. It has 2B parameters and is released under a custom license (see the model card).

HardwareLink to this section

At full FP16 precision the weights need about 4 GB of memory; 8-bit quantization brings that to roughly 2 GB. Check the VRAM tiers above to see which GPUs fit it.

PopularityLink to this section

Confucius4-R2T2 had 44,601 downloads on Hugging Face in the last month and has 608 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 Confucius4-R2T2 need?

Confucius4-R2T2 with 2B parameters needs approximately 1 GB at Q4_K_M quantization. Use our VRAM calculator for an exact estimate.

Is Confucius4-R2T2 better than other netease-youdao models?

Confucius4-R2T2 has 2B parameters with 8,192 context - a strong choice for speech-recognition.

What license is Confucius4-R2T2 under?

Confucius4-R2T2 is released under the Other license, making it suitable for most commercial and personal projects.

What hardware runs Confucius4-R2T2 well?

With 2B parameters, Confucius4-R2T2 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 Confucius4-R2T2?

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 Confucius4-R2T2?

Confucius4-R2T2 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