SQLCoder (15B) overview
SQLCoder (15B) specs
- Developer
- Defog AI
- Input
- Text
- Output
- Text
- API
- OpenAI-compatible, base URL
https://api.aimlapi.com/v1
SQLCoder (15B) Description
SQLCoder is a robust family of language models that specialize in converting natural language questions into SQL queries, surpassing the performance of models like GPT-4. With versions ranging up to 70 billion parameters, SQLCoder demonstrates exceptional ability in understanding and structuring complex data requests into SQL format. It's trained on diverse datasets involving 20,000 human-curated questions across multiple schemas, ensuring broad coverage and high accuracy.
Use Cases for the Model
SQLCoder is ideal for applications in business intelligence, data analytics platforms, and anywhere rapid, accurate translation of natural language into SQL is needed. It enhances user interfaces by allowing non-technical users to interact with databases through simple queries, thereby democratizing data access and manipulation.
How does it compare to other models?
SQLCoder uniquely outperforms similar models like GPT-4 in SQL query generation, particularly in handling complex queries across various categories such as dates, grouping, and joins. Its specialized training on SQL-focused tasks allows it to generate more accurate and efficient SQL queries compared to more generalized language models.
Tips for Maximizing Efficiency
To get the most out of SQLCoder, ensure that your queries are clear and structured. Utilize the model’s capabilities by integrating it directly into your database management tools or business intelligence software, providing users with the ability to generate dynamic reports and perform complex data analysis through simple conversational inputs.
Optimize Text Descriptions for Better Results
When using SQLCoder, providing contextually rich and well-defined questions will yield the best SQL outputs. Precision in the input queries will significantly enhance the model’s ability to generate accurate SQL commands, minimizing the need for manual adjustments.
Different Types of API Calls
SQLCoder supports various API configurations to accommodate different operational needs, whether for batch processing of queries or real-time database interactions. This flexibility ensures that SQLCoder can be effectively integrated into a range of applications, from lightweight mobile apps to complex enterprise systems.
Use cases
- Business intelligence and data analytics platforms
- Data exploration and visualization tools with natural language interfaces
- Automated SQL query generation for enterprise database management
- Support for non-expert users querying SQL databases
- Integration in analytic pipelines requiring rapid, accurate SQL generation
Capabilities
- Function calling
- Streaming
- Structured outputs
SQLCoder (15B) API pricing
| Usage | Price | Unit |
|---|---|---|
| Input | $0.315 | 1M tokens |
| Output | $0.315 | 1M tokens |
SQLCoder (15B) is unlisted on AI/ML API. The rates apply to existing integrations; the models below are current alternatives.
Prices from the AI/ML API price list, checked on Nov 4, 2026.
SQLCoder (15B) vs other models: token prices
AI/ML API input and output rates for 5 models, per million tokens.
| Model | Input | Output |
|---|---|---|
| $0.315 | $0.315 | |
| $0.0794 | $0.3174 | |
| $0.3174 | $0.3174 | |
| $0.1058 | $0.3174 | |
| $0.0794 | $0.3174 |
Related articles
SQLCoder (15B) FAQ
How much does SQLCoder (15B) cost?
SQLCoder (15B) is priced at input $0.315 / 1M, output $0.315 / 1M.
Does SQLCoder (15B) support streaming?
Yes, SQLCoder (15B) can stream responses as they are generated.
Does SQLCoder (15B) support tool calling and structured outputs?
Yes, SQLCoder (15B) supports both function calling and structured outputs.
Who created SQLCoder (15B)?
SQLCoder (15B) was built by Defog AI.


