Best AI Models for NVIDIA Jetson AGX Orin 32GB (32.0GB)
32.0 GB unified − 3.5 GB OS overhead = 28.5 GB available for AI models
32 GB positions this hardware in the professional tier for local AI. Most popular open-source models run comfortably, and even large 70B parameter models are accessible at lower quantization levels.
This memory amount is a sweet spot for enthusiasts and professionals. You can run 13B–30B models like DeepSeek R1 Distill at Q5 or Q6 quality with smooth token generation, and 7B models at near-lossless precision. The 70B class of models (Llama 3 70B, Qwen 72B) becomes possible at Q2–Q3 quantization, though with some quality trade-off. For day-to-day use with coding assistants, chat models, and reasoning tasks, this tier delivers an excellent experience.
Runs Well
- 7B–13B models at Q6–Q8 quality
- 14B–30B models at Q4–Q5 quality
- Small models (3B–7B) at FP16 precision
- Vision-language models at good quality
Challenging
- 70B models only at Q2–Q3 (noticeable quality loss)
- Large context windows with 30B+ models
What LLMs Can NVIDIA Jetson AGX Orin 32GB Run?
Showing compatibility for NVIDIA Jetson AGX Orin 32GB
| Model | Quant | VRAM | Speed | Context | Status | Grade |
|---|---|---|---|---|---|---|
| Q4_K_M | 2.9 GB9% | 46.7 t/s | 131K | EASY RUN | C30 | |
| Q4_K_M | 1.3 GB4% | 100.8 t/s | 8K | EASY RUN | D27 | |
| Q4_K_M | 5.0 GB16% | 26.7 t/s | 33K | EASY RUN | C33 | |
| Q4_K_M | 9.1 GB28% | 14.6 t/s | 16K | EASY RUN | C43 | |
| Q4_K_M | 5.3 GB17% | 25.2 t/s | 131K | EASY RUN | C34 | |
| Q4_K_M | 5.5 GB17% | 24.1 t/s | 41K | EASY RUN | C34 | |
| Q4_K_M | 7.9 GB25% | 16.8 t/s | 33K | EASY RUN | C40 | |
| Q4_K_M | 4.9 GB15% | 27.1 t/s | 33K | EASY RUN | C33 |
NVIDIA Jetson AGX Orin 32GB Specifications
- Brand
- NVIDIA
- Chip
- Orin
- Type
- AI Box
- Unified Memory
- 32.0 GB
- Memory Bandwidth
- 204.8 GB/s
- GPU Cores
- 1792
- CPU Cores
- 8
- Neural Engine
- 200.0 TOPS
- Release Date
- 2022-03-22
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Frequently Asked Questions
- Can NVIDIA Jetson AGX Orin 32GB run Llama 3 8B?
Yes, the NVIDIA Jetson AGX Orin 32GB with 32 GB unified memory can run Llama 3 8B at multiple quantization levels. At Q4_K_M (the recommended starting point), you'll get smooth token generation suitable for interactive chat and coding assistance.
- How much memory is available for AI on NVIDIA Jetson AGX Orin 32GB?
The NVIDIA Jetson AGX Orin 32GB has 32 GB unified memory. After macOS overhead (~3.5 GB), approximately 28.5 GB is available for AI models. This unified memory architecture is efficient since the GPU and CPU share the same memory pool without copy overhead.
- Is NVIDIA Jetson AGX Orin 32GB good for AI?
With 32 GB unified memory and 204.8 GB/s bandwidth, the NVIDIA Jetson AGX Orin 32GB is very good for running local LLM models. Apple Silicon's unified memory and Metal acceleration provide a premium local AI experience.
- What's the best model for NVIDIA Jetson AGX Orin 32GB?
For the NVIDIA Jetson AGX Orin 32GB, we recommend starting with Llama 3 8B at Q5_K_M for the best quality-to-speed balance, or DeepSeek R1 Distill 14B at Q4_K_M for stronger reasoning. Use Ollama or LM Studio for easy setup.
- How fast is NVIDIA Jetson AGX Orin 32GB for AI inference?
Token generation speed depends on the model and quantization. With 204.8 GB/s memory bandwidth, you can expect 20-50 tokens per second on 7B models at Q4_K_M, which is comfortable for real-time chat interaction.