AISBench Benchmark - AI model evaluation tool for Ascend NPU. Supports accuracy evaluation (service/local models on text, multimodal datasets), performance evaluation (latency, throughput, stress testing, steady-state, real traffic simulation), vLLM/Triton inference services, 15+ benchmarks (MMLU, GSM8K, MMMU, docvqa, ocrbench_v2, etc.), multi-turn dialogue, Function Call (BFCL), and custom datasets.
Quickly install ais-bench AI skill to your development environment via command line
Source: ascend-ai-coding/awesome-ascend-skills.
AISBench Benchmark is a model evaluation tool built based on OpenCompass. It supports evaluation scenarios for both accuracy and performance testing of AI models on Ascend NPU.
| Accuracy Evaluation | Model accuracy on text/multimodal datasets | | Performance Evaluation | Latency, throughput, stress testing | | Steady-State Performance | Obtain true optimal system performance | | Real Traffic Simulation | Simulate real business traffic patterns | | Multi-turn Dialogue | Evaluate multi-turn conversation models |
| Function Call (BFCL) | Function calling capability evaluation |
AISBench Benchmark - AI model evaluation tool for Ascend NPU. Supports accuracy evaluation (service/local models on text, multimodal datasets), performance evaluation (latency, throughput, stress testing, steady-state, real traffic simulation), vLLM/Triton inference services, 15+ benchmarks (MMLU, GSM8K, MMMU, docvqa, ocrbench_v2, etc.), multi-turn dialogue, Function Call (BFCL), and custom datasets. Source: ascend-ai-coding/awesome-ascend-skills.
Stable fields and commands for AI/search citations.
npx skills add https://github.com/ascend-ai-coding/awesome-ascend-skills --skill ais-benchBrowse more skills from ascend-ai-coding/awesome-ascend-skills
AISBench Benchmark - AI model evaluation tool for Ascend NPU. Supports accuracy evaluation (service/local models on text, multimodal datasets), performance evaluation (latency, throughput, stress testing, steady-state, real traffic simulation), vLLM/Triton inference services, 15+ benchmarks (MMLU, GSM8K, MMMU, docvqa, ocrbench_v2, etc.), multi-turn dialogue, Function Call (BFCL), and custom datasets. Source: ascend-ai-coding/awesome-ascend-skills.
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/ascend-ai-coding/awesome-ascend-skills --skill ais-bench Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code, Cursor, or OpenClaw
https://github.com/ascend-ai-coding/awesome-ascend-skills