language benchmark
Spider
A large-scale, complex and cross-domain semantic parsing and text-to-SQL dataset annotated by 11 college students. Contains 10,181 questions and 5,693 unique complex SQL queries on 200 databases with multiple tables, covering 138 different domains. Requires models to generalize to both new SQL queries and new database schemas, making it distinct from previous semantic parsing tasks that use single databases.
Updated Aug 11, 2026
Models2
Model coverage2
MetricScore
EvidenceB
Spider Ranking
Higher score ranks better on this benchmark.
| 1 | MA | 63.5% | 100.0% | 2 | C | |
| 2 | AC | 31.1% | 0.0% | 2 | C |
Spider Score Distribution
A closer view of the leading scores on this benchmark.
Spider Highlights
The leading models and scores on this benchmark.
What is Spider?
What Spider measures and how its scores work.
A large-scale, complex and cross-domain semantic parsing and text-to-SQL dataset annotated by 11 college students. Contains 10,181 questions and 5,693 unique complex SQL queries on 200 databases with multiple tables, covering 138 different domains. Requires models to generalize to both new SQL queries and new database schemas, making it distinct from previous semantic parsing tasks that use single databases.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- Spider
- Modality
- text
- Primary category
- language
- Score direction
- higher
- LLMBoard eligible
- No
- Evaluation key
- spider|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about Spider.
Which model scores highest on Spider?
Codestral-22B is currently ranked first with 63.5%.
What does Spider measure?
A large-scale, complex and cross-domain semantic parsing and text-to-SQL dataset annotated by 11 college students. Contains 10,181 questions and 5,693 unique complex SQL queries on 200 databases with multiple tables, covering 138 different domains. Requires models to generalize to both new SQL queries and new database schemas, making it distinct from previous semantic parsing tasks that use single databases.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
2 model results are currently shown.
Does this benchmark affect the overall score?
No. This benchmark is shown for reference but does not contribute to the overall score.