evalscope-docs

EvalScope Documentation

EvalScope is ModelScope's LLM/VLM evaluation framework providing benchmarking, performance testing, arena mode, and visualization.

• GitHub | Docs

CRITICAL: grep references/ for detailed docs. references/benchmarks/ has 153 individual benchmark files with full details, metrics, and usage examples.

Quick Start

pip install evalscope

# Evaluate a model on datasets (CLI)
evalscope eval --model Qwen/Qwen2.5-0.5B-Instruct --datasets gsm8k arc --limit 5

Evaluate OpenAI-compatible API

evalscope eval
--model qwen2.5
--eval-type openai_api
--api-url http://127.0.0.1:8801/v1
--datasets gsm8k mmlu

Performance stress test

evalscope perf --model Qwen/Qwen2.5-0.5B-Instruct --url http://127.0.0.1:8801/v1

```python
from evalscope import run_task, TaskConfig

task_cfg = TaskConfig(
    model='Qwen/Qwen2.5-0.5B-Instruct',
    datasets=['gsm8k', 'arc'],
    limit=5,
    generation_config={'max_tokens': 1024, 'temperature': 0.0}
)
run_task(task_cfg)

Key Topics

Get Started

• references/get_started/installation.md — Installation
• references/get_started/basic_usage.md — Quick start guide
• references/get_started/parameters.md — All CLI/TaskConfig parameters
• references/get_started/faq.md — FAQ

Supported Datasets

• references/get_started/supported_dataset/index.md — Dataset overview
• references/get_started/supported_dataset/llm.md — LLM benchmarks (MMLU, GSM8K, HumanEval, etc.)
• references/get_started/supported_dataset/vlm.md — VLM benchmarks
• references/get_started/supported_dataset/agent.md — Agent benchmarks
• references/get_started/supported_dataset/aigc.md — AIGC (T2I) benchmarks
• references/benchmarks/ — 153 individual benchmark docs with metrics, examples, prompt templates
• references/datasets.csv — Full registry (190 datasets: name, backends, tags, metrics, subsets)

Backends

• references/user_guides/backend/index.md — Backend selection guide
• references/user_guides/backend/opencompass_backend.md — OpenCompass backend
• references/user_guides/backend/vlmevalkit_backend.md — VLMEvalKit backend
• references/user_guides/backend/rageval_backend/ — RAGEval (RAGAS, MTEB, CLIP)

Performance Testing

• references/user_guides/stress_test/index.md — Stress test overview
• references/user_guides/stress_test/quick_start.md — Quick start
• references/user_guides/stress_test/parameters.md — All perf parameters
• references/user_guides/stress_test/examples.md — Examples

Advanced

• references/advanced_guides/custom_dataset/ — Custom datasets (LLM, VLM, CLIP, Embedding)
• references/advanced_guides/collection/ — Dataset collection management
• references/advanced_guides/add_benchmark.md — Add custom benchmark
• references/advanced_guides/custom_model.md — Custom model integration
• references/user_guides/arena.md — Arena (model comparison) mode
• references/user_guides/sandbox.md — Sandbox evaluation
• references/user_guides/service.md — Service mode (online API eval)
• references/get_started/visualization.md — WebUI visualization

Best Practices

• references/best_practice/ — Qwen3, DeepSeek-R1, QwQ, GPT, VLM, T2I evaluation guides
• references/third_party/ — SWE-Bench, BFCL, ToolBench, LongWriter, NeedleHaystack

References

• references/ — 228 doc files from docs/en/
• references/benchmarks/ — 153 benchmark docs (name, dataset_id, metrics, examples, usage)
• references/datasets.csv — Full dataset registry (190 datasets)