DeepSeek Coder 6.7B Instruct vs SQLCoder 7B v2
Compare the listed model data for DeepSeek Coder 6.7B Instruct by deepseek-ai and SQLCoder 7B v2 by defog. Benchmark and pricing records are not a controlled test and may change.
Data last updated: 2026-10-16. Verify current model details with each provider.
What the listed data says
DeepSeek Coder 6.7B Instruct: 16K tokens; SQLCoder 7B v2: 8K tokens. DeepSeek Coder 6.7B Instruct has the larger listed context window. DeepSeek Coder 6.7B Instruct is listed for coding; SQLCoder 7B v2 is listed for coding. Shared catalog benchmark entries: No shared benchmark labels are listed in these model records. These records are reference data, not a controlled head-to-head test; verify current pricing and specifications with each provider.
Catalog source links
Use these model and provider links to verify current specifications, pricing, and availability.
Computed differences from catalog data
- The listed context windows are 16K tokens and 8K tokens; the larger is 2× the smaller.
- No shared benchmark labels are present in both catalog records.
- The first listed parameter quantities are 6.7B and 7B; the larger quantity is 1.04× the smaller. Total and active MoE parameters are not directly equivalent.
- A release-date gap cannot be calculated from the catalog values (DeepSeek Coder 6.7B Instruct: November 2023; SQLCoder 7B v2: 2024).
Cost example: 1M input and 1M output tokens
A cost example for 1M input plus 1M output tokens cannot be calculated reliably because separate numeric input and output rates are not listed for both models.
Choose DeepSeek Coder 6.7B Instruct if…
Choose DeepSeek Coder 6.7B Instruct when your task aligns with catalog-listed uses or strengths such as Legacy code completion integrations, Resource-constrained code deployments, Strong coding at 6.7B for 2023 — competitive with GPT-3.5 on code, 86+ programming languages.
Choose SQLCoder 7B v2 if…
Choose SQLCoder 7B v2 when your task aligns with catalog-listed uses or strengths such as Natural language database interfaces, Self-service BI tools for non-technical analysts, Data warehouse SQL generation, State-of-the-art text-to-SQL at 7B scale.
DeepSeek Coder 6.7B Instruct
DeepSeek's compact code model trained on 2T tokens of code — strong at completion, refactoring, and bug fixes across 80+ languages.
Parameters: 6.7B
Context: 16K tokens
Catalog pricing: DeepSeek Coder License — free for commercial use
SQLCoder 7B v2
Defog's SQLCoder 7B — generates accurate SQL from natural-language questions over your database schema. Beats GPT-4 on SQL benchmarks.
Parameters: 7B
Context: 8K tokens
Catalog pricing: CC-BY-SA 4.0 — free
Feature Comparison — DeepSeek Coder 6.7B Instruct vs SQLCoder 7B v2
| Specification | DeepSeek Coder 6.7B Instruct | SQLCoder 7B v2 |
|---|---|---|
| Provider | deepseek-ai | defog |
| Parameters | 6.7B | 7B |
| Context window | 16K tokens | 8K tokens |
| Maximum output | Not listed | Not listed |
| Catalog pricing | DeepSeek Coder License — free for commercial use | CC-BY-SA 4.0 — free |
| Listed input/output cost per 1M tokens | Separate numeric input/output rates not listed | Separate numeric input/output rates not listed |
| License | DeepSeek Coder License | CC-BY-SA 4.0 |
| Coding support | Listed | Listed |
| Reasoning support | Not listed | Not listed |
| Vision input | Not listed | Not listed |
| Multimodal | Not listed | Not listed |
| Open weights | Yes | Yes |
Figures are transcribed from LITHOVEX model records. Benchmark versions and evaluation setups may differ; pricing and specifications can change. Check each provider's current documentation before making a decision.
Frequently Asked Questions
What is different between DeepSeek Coder 6.7B Instruct and SQLCoder 7B v2?
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What are the listed costs per million tokens for DeepSeek Coder 6.7B Instruct and SQLCoder 7B v2?
How far apart are the listed release dates for DeepSeek Coder 6.7B Instruct and SQLCoder 7B v2?
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Explore these models and related comparisons
Read the DeepSeek Coder 6.7B Instruct model profile and SQLCoder 7B v2 model profile, or browse the model directory.