Wooha! TrueNAS Scale 25.10 running Ollama AI local models on my Old PowerEdge r720 128 GB RAM with RTX 5070 12 GB VRAM.
Stats:
total duration: 13.47505831s
load duration: 391.896386ms
prompt eval count: 51 token(s)
prompt eval duration: 27.646026ms
prompt eval rate: 1844.75 tokens/s
eval count: 709 token(s)
eval duration: 11.208734619s
eval rate: 63.25 tokens/s
Full request:
ollama run qwen2.5:14b “Write a detailed 600-word blog post about why Blackwell GPUs are excellent for local AI inference.” --verbose
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Why Blackwell GPUs Are Excellent for Local AI Inference
The rapid advancement of artificial intelligence (AI) has led to an explosion in the demand for
powerful hardware that can handle complex tasks such as machine learning, deep learning, and other
advanced computations at the edge or on-device. Among these devices, NVIDIA’s latest GPU
generation, known as Blackwell GPUs, stands out due to their exceptional capabilities tailored for
local AI inference. Here are several reasons why these GPUs have become an indispensable part of
modern AI ecosystems.
1. Superior Performance
Blackwell GPUs offer unparalleled performance thanks to their advanced architecture and increased
core count compared to previous generations like the Ampere series. These GPUs leverage the latest
NVIDIA CUDA cores, which enable faster execution of parallel computations—a critical aspect for
real-time inference in edge devices. The enhanced tensor cores further accelerate matrix
operations commonly used in deep learning models, making them highly efficient for AI workloads.
2. Power Efficiency
Energy consumption is a significant concern with traditional GPUs, especially when deployed in
mobile or embedded systems where power budgets are tight. Blackwell GPUs address this issue by
offering significantly improved power efficiency through architectural optimizations and advanced
manufacturing processes (such as TSMC’s N4 process technology). This means they can deliver high
performance without compromising on battery life, making them ideal for devices like smartphones,
tablets, and edge servers.
3. Enhanced AI Inference Capabilities
Blackwell GPUs come equipped with NVIDIA’s latest TensorRT software suite, which is specifically
designed to optimize the deployment of deep learning models in real-world applications. The
inclusion of new features such as DLBoost and INT4 data types helps reduce latency while
maintaining high accuracy levels, thus ensuring smooth user experiences across various AI-driven
services.
4. Versatility Across Use Cases
From healthcare diagnostics through computer vision applications, to autonomous vehicles requiring
continuous processing at the edge, Blackwell GPUs cater to a wide range of use cases due to their
versatility and scalability. They support both training and inference operations, allowing
developers to fine-tune models locally before deploying them in production environments. This
flexibility is crucial for industries where rapid prototyping and iterative development cycles are
commonplace.
5. Integration with Ecosystems
NVIDIA’s strong ecosystem presence ensures that Blackwell GPUs work seamlessly across various
software frameworks and tools commonly used in AI projects. Compatibility with TensorFlow,
PyTorch, ONNX (Open Neural Network Exchange), and other platforms simplifies the deployment
process for developers while providing robust support for diverse use cases.
6. Security Enhancements
In an era where data security is paramount, Blackwell GPUs introduce hardware-based protections
designed to safeguard sensitive information processed during AI inference tasks. Features like
secure boot, encrypted memory, and virtualization support ensure that confidential data remains
protected throughout its lifecycle within the GPU environment.
Conclusion
The advent of Blackwell GPUs represents a significant leap forward in local AI processing
capabilities. Their combination of superior performance, power efficiency, advanced AI-specific
optimizations, versatility across multiple applications, seamless integration with existing
ecosystems, and enhanced security features make them an ideal choice for businesses looking to
leverage cutting-edge AI technologies without the need for cloud connectivity or extensive
infrastructure investments. As more industries adopt on-device intelligence solutions, Blackwell
GPUs are poised to play a pivotal role in driving innovation forward.
In summary, whether you’re developing AI-driven applications for consumer electronics, automotive
systems, or enterprise environments, integrating Blackwell GPUs into your projects can offer
unparalleled benefits in terms of speed, efficiency, and functionality.
total duration: 13.47505831s
load duration: 391.896386ms
prompt eval count: 51 token(s)
prompt eval duration: 27.646026ms
prompt eval rate: 1844.75 tokens/s
eval count: 709 token(s)
eval duration: 11.208734619s
eval rate: 63.25 tokens/s
