Search Results for "benchmarks" - Page 8
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Showing 440 open source projects for "benchmarks"
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Surya
Implementation of the Surya Foundation Model for Heliophysics
Surya is an open‑source, AI‑based foundation model for heliophysics developed collaboratively by NASA (via the IMPACT AI team) and IBM. Named after the Sanskrit word for “sun,” Surya is trained on nine years of high‑resolution solar imagery from NASA’s Solar Dynamics Observatory (SDO). It is designed to forecast solar phenomena—such as flares, solar wind, irradiance, and active region behavior—by predicting future solar images with a sophisticated long–short vision transformer architecture,... -
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ObjectBox Java Database
Java and Android Database - fast and lightweight without any ORM
...Get fast access to the data you need across Embedded Devices, IoT, and Mobile. ObjectBox is 10x faster than any alternative, with high-speed data ingestion that increases response times. Check out our benchmarks. ObjectBox’ out-of-the-box synchronization makes data available when needed where needed, eliminating data islands and improving data flow. Develop applications that work on- and offline, independently from a constant Internet connection, providing an “always-on”-feeling. Accelerate time-to-market with ObjectBox’ easy and super fast native language APIs, that bring the fun back to coding. ... -
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Suave
Suave is a simple web development F# library
...We have a NuGet ready for your testing needs; Suave is an excellent server for running in-process integration tests, as it's very fast to spawn. On an ordinary laptop, running hundreds of randomized tests and micro-benchmarks as well as all Suave unit tests, take about 5 seconds on mono. -
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esbuild-loader
Speed up your Webpack build with esbuild
...It is also recommended to enable isolatedModules and esModuleInterop options in your tsconfig by the esbuild docs. You can replace JS minifiers like Terser or UglifyJs. Checkout the benchmarks to see how much faster esbuild is. The target option tells esbuild that it can use newer JS syntax to perform better minification. -
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Qwen2.5-Omni
Capable of understanding text, audio, vision, video
...It supports “Thinker-Talker” architecture, and introduces innovations for aligning modalities over time (for example synchronizing video/audio), robust speech generation, and low-VRAM/quantized versions to make usage more accessible. It holds state-of-the-art performance in many multimodal benchmarks, particularly spoken language understanding, audio reasoning, image/video understanding, etc. Very strong benchmark performance across modalities (audio understanding, speech recognition, image/video reasoning) and often outperforming or matching single-modality models at a similar scale. Real-time streaming responses, including natural speech synthesis (text-to-speech) and chunked inputs for low latency interaction. -
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Qwen3-Omni
Qwen3-omni is a natively end-to-end, omni-modal LLM
...The model supports 119 text languages, 19 speech input languages, and 10 speech output languages. It achieves state-of-the-art results: across 36 audio and audio-visual benchmarks, it hits open-source SOTA on 32 and overall SOTA on 22, outperforming or matching strong closed-source models such as Gemini-2.5 Pro and GPT-4o. To reduce latency, especially in audio/video streaming, Talker predicts discrete speech codecs via a multi-codebook scheme and replaces heavier diffusion approaches. -
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Code-Mode
Plug-and-play library to enable agents to call MCP and UTCP tools
...This approach can dramatically reduce the number of tool-call iterations needed in complex workflows, turning multi-step call chains into a single code execution with internal branching and loops. The repository contains both TypeScript and Python libraries, plus a code-mode-mcp component for integrating with MCP and UTCP ecosystems. Benchmarks in the README highlight improvements in latency and token cost for scenarios involving multiple tools, showing that code execution often outperforms traditional JSON-based function calling. -
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KrakenD
High-performance, stateless, declarative, API Gateway written in Go.
...Our customers with massive usage face the networking limits while KrakenD still keeps a low consumption of resources. But don't take our word for granted, do your own benchmarks. All KrakenD endpoint configuration is stored in a plain text .json configuration file. You can edit this file by hand or design your API interface visually using the KrakenDesigner. -
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Step-Audio 2
Multi-modal large language model designed for audio understanding
Step-Audio2 is an advanced, end-to-end multimodal large language model designed for high-fidelity audio understanding and natural speech conversation: unlike many pipelines that separate speech recognition, processing, and synthesis, Step-Audio2 processes raw audio, reasons about semantic and paralinguistic content (like emotion, speaker characteristics, non-verbal cues), and can generate contextually appropriate responses — including potentially generating or transforming audio output. It... -
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HunyuanWorld-Voyager
RGBD video generation model conditioned on camera input
...To support training, the team built a scalable data engine that automatically curates large video datasets with camera pose estimation and metric depth prediction. As a result, Voyager delivers state-of-the-art performance on world exploration benchmarks while maintaining photometric, style, and 3D consistency. -
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ClickHouse
A fast open-source OLAP database management system
ClickHouse® is a fast, open-source column-oriented database management system that can generate analytical data reports through SQL queries in real time. According to several independent benchmarks, it far exceeds other comparable column-oriented database management systems, working even up to 1000 times faster. It is able to process hundreds of millions to more than a billion rows and tens of gigabytes of data per single server per second. Apart from its blazing speed, ClickHouse is highly reliable and fault tolerant. It supports multi-master asynchronous replication with the option of being deployed across multiple datacenters. ... -
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GLM-4.6V
GLM-4.6V/4.5V/4.1V-Thinking, towards versatile multimodal reasoning
...Its architecture supports a very large context window (on the order of 128K tokens during training), which lets it handle complex multimodal inputs like long documents, multi-page reports, or video transcripts, while maintaining coherence across extended content. In benchmarks and internal evaluations, GLM-4.6V achieves state-of-the-art (SoTA) performance among models of comparable parameter scale on multimodal reasoning. -
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DGL
Python package built to ease deep learning on graph
Build your models with PyTorch, TensorFlow or Apache MXNet. Fast and memory-efficient message passing primitives for training Graph Neural Networks. Scale to giant graphs via multi-GPU acceleration and distributed training infrastructure. DGL empowers a variety of domain-specific projects including DGL-KE for learning large-scale knowledge graph embeddings, DGL-LifeSci for bioinformatics and cheminformatics, and many others. We are keen to bringing graphs closer to deep learning researchers.... -
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CodeGeeX4
CodeGeeX4-ALL-9B, a versatile model for all AI software development
...Compared to its predecessors, CodeGeeX4 introduces improved reasoning, stronger alignment with developer needs, and better performance on real-world programming benchmarks. It supports tasks such as code completion, generation from natural language descriptions, code translation, bug fixing, and explanation. The repository provides model checkpoints, inference examples, and fine-tuning guides, making it adaptable for both research and practical software development workflows. With its open release, CodeGeeX4 aims to provide a transparent alternative to proprietary coding assistants while advancing the field of AI-assisted programming. -
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RBush
High-performance JavaScript R-tree-based 2D spatial index
...It's most commonly used in maps and data visualizations. The demos contain visualization of trees generated from 50k bulk-loaded random points. Open web console to see benchmarks; click on buttons to insert or remove items; click to perform search under the cursor. An optional argument to RBush defines the maximum number of entries in a tree node. 9 (used by default) is a reasonable choice for most applications. Higher value means faster insertion and slower search, and vice versa. -
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CodeGeeX2
CodeGeeX2: A More Powerful Multilingual Code Generation Model
...Compared to the first generation, it delivers a significant boost in programming ability across multiple languages, outperforming even larger models like StarCoder-15B in some benchmarks despite having only 6B parameters. The model excels at code generation, translation, summarization, debugging, and comment generation, and it supports over 100 programming languages. With improved inference efficiency, quantization options, and multi-query/flash attention, CodeGeeX2 achieves faster generation speeds and lightweight deployment, requiring as little as 6GB GPU memory at INT4 precision. ... -
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TextDistance
Compute distance between sequences
...Install text distance with extras for this feature. Textdistance use benchmark results for algorithm optimization and try to call the fastest external lib first (if possible). TextDistance show benchmarks results table for your system and saves libraries priorities into the libraries.json file in TextDistance's folder. This file will be used by text distance for calling the fastest algorithm implementation. Default libraries.json is already included in the package. -
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OpenFace Face Recognition
Face recognition with deep neural networks
...Any opinions, findings, conclusions or recommendations expressed in this material are those of the authors and should not be attributed to their employers or funding sources. Accuracies from research papers have just begun to surpass human accuracies on some benchmarks. The accuracies of open source face recognition systems lag behind the state-of-the-art. See our accuracy comparisons on the famous LFW benchmark. -
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Novabench
Benchmark CPU, GPU, memory, and storage
Novabench is a computer benchmarking software that helps users evaluate and compare the performance of their system’s CPU, GPU, memory, and storage. It offers rapid testing, enabling comparisons across millions of devices and providing insights for troubleshooting, upgrades, and performance optimization. -
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imagemoz-core
AI Metadata Framework and Generative Tool Infrastructure.
Technical repository for the ImAgeMoz AI ecosystem. This project hosts standardized JSON metadata structures for generative AI tools and prompt engineering validation scripts. It serves as the core data layer for the ImAgeMoz directory." -
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Hard Disk Sentinel
Hard drive monitoring, disk health, and temperature monitoring tool
Hard Disk Sentinel (HDSentinel) is a comprehensive hard drive monitoring software designed to track the health, performance, and temperature of various types of storage devices including hard disks, SSDs, and external drives. It provides real-time monitoring and detailed reports to help prevent data loss by identifying potential hardware issues early. With a user-friendly interface, it displays critical data such as drive health status, temperature levels, and potential errors, allowing... -
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LinAsm
Collection of fast and optimized assembly libraries for x86-64 Linux
...It implements many common and widely used algorithms for array manipulations: searching, sorting, arithmetic and vector operations, unit conversions; fast mathematical and statistic functions; numbers and time converting algorithms; finite impulse response (FIR) digital filters; spectrum analysis algorithms, Fast Hartley transformation; CPU cache friendly functions and extremely fast abstract data types (ADT) such as hash tables b-trees, and much more. LinAsm libraries are written on FASM assembly language. They are stable and have appropriate benchmarks for many units. All libraries are well documented and grouped by their functionality. To get more information about this library, please visit the official web site: http://linasm.sourceforge.net -
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powerMAX
powerMAX is a CPU and GPU burn-in test
...The utility supports dedicated CPU tests—SSE or AVX—and a demanding GPU 3D rendering test, with the option to run both simultaneously for full-system power load evaluation. Because it does not generate scores or benchmarks, powerMAX is strictly a stress-testing tool rather than a performance comparison utility. The software requires no installation, leaves no system traces, and runs on any Windows system from Windows 7 onward. Users must operate powerMAX at their own risk, as the extreme loads can expose component flaws and potentially cause irreversible hardware damage. -
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WinDeployStudio
Windows toolkit for bootable USB, To Go, and disk diagnostics.
WinDeploy Studio is a Windows desktop toolkit for creating Windows installation USB drives, validating and writing Linux ISOHybrid media, and building portable Windows To Go workspaces. It includes strict preflight checks for supported experimental Linux To Go profiles, native drive benchmarks, disk diagnostics, image resources, logs, and AI-assisted troubleshooting. Destructive operations are bound to the selected external disk and revalidated before writing. The application supports 11 interface languages and is distributed under the MIT License. -
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TAME LLM
Traditional Mandarin LLMs for Taiwan
...The training pipeline leverages high-performance computing infrastructure and frameworks such as NVIDIA NeMo and Megatron to enable large-scale model training. Taiwan-LLM aims to improve language understanding and generation for Traditional Mandarin users by incorporating region-specific datasets and evaluation benchmarks.
