reasoning benchmark
Spider Leaderboard
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 17, 2026
Models2
Model coverage2
MetricScore
EvidenceB
Spider Ranking
Higher score ranks better on this benchmark.
Sort by
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelMA | Score63.5% | Percentile100.0% | Participants2 | EvidenceC | Evaluated |
| Rank02 | ModelAC | Score31.1% | Percentile0.0% | Participants2 | EvidenceC | Evaluated |
Spider Highlights
The leading models and scores on this benchmark.
Spider Score Distribution
A closer view of the leading scores on this benchmark.
The Top AI Models for Spider
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
Ranking basisThis spider AI model leaderboard uses descending score in the benchmark's original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.
- 01MACodestral-22BMistral AI
- Score
- 63.5%
Strengths
- Ranks #1 of 2 compared models
- 100th percentile on this benchmark
- C evidence result
Considerations
- This result measures Spider, not total model capability
- 02ACQwen3-Coder 480B A35B InstructAlibaba Cloud / Qwen Team
- Score
- 31.1%
- Price
- $1.5 input / $7.5 output per 1M tokens
Strengths
- Ranks #2 of 2 compared models
- 0th percentile on this benchmark
- C evidence result
Considerations
- This result measures Spider, not total model capability
Selection summary
Best AI Models for Spider
Codestral-22B currently leads Spider with 63.5%. It is the top model on this specific benchmark, while the best LLM for the broader task should also be checked against other benchmarks, price and runtime.
Use this leaderboard with the supporting benchmark results and coverage details above. A leaderboard position summarizes the selected ranking signal; it does not replace workload-specific testing.
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
- reasoning
- 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.