Model Releases
Voice conversations between Gemma4 12B and E2B on GPU and Jetson Orin
Gemma 4 12B runs on an RTX PRO 4500 Blackwell. Gemma 4 E2B run on a Jetson Orin NX 16GB; similar performance is expected on a Jetson Orin Nano Super 8GB. Both systems use a reSpeaker Flex 4-mic array
Gemma 4 12B runs on an RTX PRO 4500 Blackwell. Gemma 4 E2B run on a Jetson Orin NX 16GB; similar performance is expected on a Jetson Orin Nano Super 8GB. Both systems use a reSpeaker Flex 4-mic array and a 3W speaker. Inference is handled by Cortexist Little Gemma, a small LLM engine written in C for CUDA devices. On Jetson Orin it is faster than llama.cpp, and no degradation after long voice prompt. The pipeline supports lip sync, expressions, and gestures. Everything is open source. They talk to humans too. The engine source code: https://github.com/cortexist/little-gemma submitted by /u/cortexist [link] [comments]
Related
- Gemma 4 VLA Demo on Jetson Orin Nano Super
- Gemma 4 12B Q3: +8.55% Coding Performance From Tensor-Level Quantization Allocation
- I put Gemma 4 E4B and E2B into an e-reader so I can ask my weird questions and share my thoughts in private directly in app.
Source: r/LocalLLaMA | 2026-09-08