Search Results for "gpu-z"
Sort By:
Showing 13 open source projects for "gpu-z"
View related business solutions-
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
-
Stop Cyber Threats with VM-Series Next-Gen Firewall on AzureGain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
-
1
llmfit
157 models, 30 providers, one command to find what runs on hardware
llmfit is a terminal-based utility that helps developers determine which large language models can realistically run on their local hardware by analyzing system resources and model requirements. The tool automatically detects CPU, RAM, GPU, and VRAM specifications, then ranks available models based on performance factors such as speed, quality, and memory fit. It provides both an interactive terminal user interface and a traditional CLI mode, enabling flexible workflows for different user preferences. llmfit also supports advanced configurations including multi-GPU setups, mixture-of-experts architectures, and dynamic quantization recommendations. ... -
2
Zed
High-performance, multiplayer code editor from the creators of Atom
Zed is a next-generation code editor designed for high-performance collaboration with humans and AI. Written from scratch in Rust to efficiently leverage multiple CPU cores and your GPU. Integrate upcoming LLMs into your workflow to generate, transform, and analyze code. Chat with teammates, write notes together, and share your screen and project. Multibuffers compose excerpts from across the codebase in one editable surface. Evaluate code inline via Jupyter runtimes and collaboratively edit notebooks. Support for many languages via Tree-sitter, WebAssembly, and the Language Server Protocol. ... -
3
OpenFang
Open-source Agent Operating System
...It aims to move beyond simple chat-based agents by providing infrastructure for persistent agent memory, task coordination, and scalable execution. The system is positioned as a foundation for building advanced AI tooling, particularly in environments that require tight integration with GPU workflows and modern AI pipelines. OpenFang emphasizes modularity and extensibility so developers can plug in custom agents, tools, or execution backends. Overall, the project represents an emerging class of “agent OS” platforms that treat AI agents as first-class computational actors rather than isolated scripts. -
4
shimmy
Python-free Rust inference server
...It supports modern model formats such as GGUF and SafeTensors and can automatically discover models stored locally or in common directories used by other AI tools. Advanced capabilities include CPU offloading for Mixture-of-Experts models and GPU acceleration, enabling large models to run on consumer hardware with limited VRAM. -
$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
-
5
uzu
A high-performance inference engine for AI models
...Written primarily in Rust and leveraging Apple’s Metal framework, the project focuses on maximizing performance when executing large language models and other AI workloads on devices such as Mac computers with M-series chips. The engine implements a hybrid architecture in which model layers can be executed either as custom GPU kernels or through Apple’s MPSGraph API, allowing it to balance performance and compatibility depending on the workload. By utilizing Apple’s unified memory architecture, uzu reduces memory copying overhead and improves inference throughput for local AI workloads. The system includes a simple high-level API that enables developers to run models, create inference sessions, and generate outputs with minimal configuration. -
6
OpenShell
OpenShell is the safe, private runtime for autonomous AI agents.
OpenShell is an open-source runtime designed to safely run autonomous AI agents in isolated environments. Developed by NVIDIA, it provides sandboxed execution spaces that protect system resources, credentials, and data from unauthorized access. Each agent runs inside a containerized sandbox governed by declarative YAML security policies that control network access, file permissions, and process behavior. The platform includes a gateway service that manages sandbox lifecycles and routes AI... -
7
MusicGPT
Generate music based on natural language prompts using LLMs
MusicGPT is an open-source application designed to generate music from natural language prompts using locally executed artificial intelligence models. The software allows users to run advanced music generation systems directly on their own devices without requiring heavy dependencies such as Python or full machine learning frameworks. Instead, it provides a lightweight environment capable of executing music generation models locally on CPUs or GPUs while maintaining strong performance across... -
8
Cog
Package and deploy machine learning models using Docker containers
...Developers can define the runtime environment, dependencies, and Python versions required for their models, allowing Cog to build a consistent container environment that follows best practices. Cog also resolves compatibility issues between frameworks and GPU libraries by automatically selecting compatible combinations of CUDA, cuDNN, and machine learning frameworks such as PyTorch or TensorFlow. Cog automatically generates a RESTful HTTP API for running predictions, enabling models to be accessed programmatically through a built-in prediction server. -
9
ort
Fast ML inference & training for ONNX models in Rust
ort is a high-performance Rust library that provides bindings to ONNX Runtime, enabling developers to run machine learning inference and training workflows directly within Rust applications using the standardized ONNX model format. It is designed to bridge the gap between modern machine learning frameworks and systems programming by offering a safe, ergonomic API for executing models originally built in ecosystems like PyTorch, TensorFlow, or scikit-learn. The library emphasizes speed and... -
Atera - an All-in-one platform for IT managementYour IT essentials, integrated & elevated. Take your IT management from automated to autonomous, download Atera's agent to start your free trial!
-
10
PostgresML
The GPU-powered AI application database
PostgresML is a complete platform in a PostgreSQL extension. Build simpler, faster, and more scalable models right inside your database. Explore the SDK and test open source models in our hosted database. Combine and automate the entire workflow from embedding generation to indexing and querying for the simplest (and fastest) knowledge-based chatbot implementation. Leverage multiple types of natural language processing and machine learning models such as vector search and personalization... -
11
pipeless
A computer vision framework to create and deploy apps in minutes
...You can easily use industry-standard models, such as YOLO, or load your custom model in one of the supported inference runtimes. Pipeless ships some of the most popular inference runtimes, such as the ONNX Runtime, allowing you to run inference with high performance on CPU or GPU out-of-the-box. You can deploy your Pipeless application with a single command to edge and IoT devices or the cloud. -
12
SIG Rust
Rust language bindings for TensorFlow
SIG Rust provides idiomatic Rust bindings for TensorFlow, making it possible for developers to work with TensorFlow functionality from within the Rust programming language. Rather than replacing TensorFlow itself, it acts as an integration layer that connects Rust applications to the TensorFlow C API. The repository is designed for developers who want Rust’s performance, safety, and systems programming strengths while still accessing TensorFlow’s machine learning capabilities. It includes... -
13
dfdx
Deep learning in Rust, with shape checked tensors and neural networks
Deep learning in Rust, with shape-checked tensors and neural networks. Ergonomics & safety focused deep learning in Rust.
- Previous
- You're on page 1
- Next
