embedl/Cosmos-Reason2-2B-W4A16
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Embedl develops advanced tools and algorithms for Edge AI. Our mission is to make AI models run faster, more energy-efficient, and reliably across diverse hardware platforms, while significantly reducing development time.
We help teams deploy high-performance AI on real-world, resource-constrained devices.
Pre-optimized models that can be used off-the-shelf or customized for specific hardware target supported by the embedl-models package.
First release highlights:
Device: Nvidia Jetson Thor
| Model | Generation speed (tokens/s) |
|---|---|
| embedl/Llama-3.2-3B-Instruct-FlashHead-W4A16 | 100 |
| Llama-3.2-3B-Instruct-W4A16* | 80 |
| RedHatAI/Llama-3.2-3B-Instruct-FP8 | 64 |
| meta-llama/Llama-3.2-3B-Instruct | 37 |
*Embedl quantized model for benchmarking similar to the FlashHead-W4A16 but without the faster FlashHead and custom generation loop.
Headquarters (Sweden)
Gamla Almedalsvägen 39
412 63 Gothenburg, Sweden
Email: contact@embedl.com