Easy benchmarking of all publicly accessible implementations of convnets
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Serve large Qwen models fast on the GPUs you actually own. Qwen3.8-27B on a single 24 GB card with vLLM: 127 tok/s single-user (381 when the answer quotes the prompt), ~1,035 tok/s at 64 concurrent, 150k-262k context. vLLM patches, requant pipeline, benchmarks.
- kv-cache
- llm-inference
- local-llm
- quantization
Load and performance benchmark tool
- python
- load-testing
- performance
- performance-test
Your Everyday Threat Intelligence
- infosec
- threatintel
- threat-sharing
- threat-hunting
Benchmark for tracking model capability after release.
A deep learning toolkit for healthcare AI: EHR (MIMIC, eICU, OMOP), clinical text, signals and imaging. 30+ models, reproducible pipelines.
- healthcare
- data-mining
- deep-learning
- preprocessing
The community's most comprehensive, continuously-updated index of research on Large Language Models for software vulnerability detection — papers across function-level, repository-level, agentic, and smart-contract detection, plus datasets, benchmarks, and surveys.
- awesome-list
- code-security
- large-language-models
- llm
Computational framework for reinforcement learning in traffic control
- reinforcement-learning
- traffic-control
- benchmark
- autonomous
A clinical decision-evidence benchmark: pull the one fact an answer rests on, and see whether the assistant's action moves with the evidence. Built on HealthBench.
Python Performance Benchmark Suite
- python
- performance
- benchmark
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models
- machine-learning
- generative-models
- drug-discovery
- benchmark
Open, source-backed catalog of computer-use agents: reviewed papers, GUI models, datasets, benchmarks, tools, and reusable JSONL/SQLite data.
- agent-evaluation
- agentic-ai
- ai-agents
- awesome
Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology.
- deep-learning
- protein-sequences
- protein-structure
- semi-supervised-learning
TranslatedSprix AI at 屿智同行 (Yuzhi Tongxing, "island wisdom traveling together") × 保研岛 (Baoyan Dao, "Baoyan Island") — an open-source benchmark for AI agents in Baoyan advising and application planning.
🔥 The first-ever interactive streaming video generation benchmark.
- avatar-performance
- interaction-streaming-video
- real-time-video-editing
- streaming-video-generation
Classify music genre from a 10 second sound stream using a Neural Network.
- deep-learning
- music-genre-classification
- paper
- tensorflow
Benchmarks for generative chemistry
RNNLG is an open source benchmark toolkit for Natural Language Generation (NLG) in spoken dialogue system application domains. It is released by Tsung-Hsien (Shawn) Wen from Cambridge Dialogue Systems Group under Apache License 2.0.
- natural-language-processing
- natural-language-generation
- nlg-dataset
- deep-learning
A lightweight Python SDK and CLI for evaluating recursive self-improvement (RSI) methods across agent benchmarks.
- ai-agents
- benchmarking
- llm-evaluation
- python
Benchmarking analysis of data integration tools
A 4B grounding foundation model for physical intelligence. Unifies detection, referring, pointing, OCR, GUI, and layout grounding, achieving SOTA overall across 34 benchmarks and improving robot generalization and data efficiency in controlled evaluations.
- embodied-ai
- gui-grounding
- object-detection
- ocr
Browser automation engine benchmark - Test bypass rates, performance & stealth against Cloudflare, DataDome, reCAPTCHA, Kasada, Imperva, Akamai, PerimeterX and other bot detection systems. Find the best browser for scraping.
- anti-detect
- antidetect-browser
- automation
- browser
:sunrise: A comprehensive, cutting-edge open-source framework for next-generation Transformers/LLM, with compute-matched benchmarking and a platform for autonomous architecture research.
- auto-research
- benchmark
- deep-learning
- language-models
AgML is a centralized framework for agricultural machine learning. AgML provides access to public agricultural datasets for common agricultural deep learning tasks, with standard benchmarks and pretrained models, as well the ability to generate synthetic data and annotations.
- deep-learning
- agriculture
- pytorch
- dataset