head-to-head
Ling-3.0-flash vs Google: Gemini 3.6 Flash
Side-by-side comparison of specs, pricing, benchmark scores, and task rankings. Updated 2026-08-18.
| Ling-3.0-flash | Google: Gemini 3.6 Flash | |
|---|---|---|
| Vendor | inclusionai | |
| Quality Score | 100 | 100 |
| Benchmark Score | 64.4 | 84.4 |
| Input Price | $0.02/M | $0.75/M |
| Output Price | $0.06/M | $3.75/M |
| Context Window | 262,144 | 1,048,576 |
| Max Output | 32,768 | 65,536 |
| Tool Calling | ✓ | ✓ |
| Structured Output | ✓ | ✓ |
| Reasoning Mode | ✓ | ✓ |
| Vision | - | ✓ |
| Audio | - | ✓ |
| Benchmark Scores | ||
| ai_index | 62.4 | 85.1 |
| ai_index_agentic | 48.4 | 66.8 |
| ai_index_coding | 83.6 | 100.0 |
Who wins by task?
| Task | Ling-3.0-flash | Google: Gemini 3.6 Flash |
|---|---|---|
| SQL Generation | 159 | 170 |
| Code Review | 152 | 165 |
| Code Completion | 130 | 132 |
| Code Refactoring | 148 | 163 |
| Bug Fixing | 162 | 178 |
| Unit Test Generation | 144 | 153 |
| Code Documentation | 135 | 142 |
| Regex Writing | 132 | 135 |
| CI/CD Pipelines | 135 | 143 |
| Frontend Component Design | 110 | 145 |
| Data Analysis | 158 | 168 |
| CSV / Spreadsheet Cleanup | 145 | 154 |
| ETL Scripting | 142 | 153 |
| JSON Extraction | 146 | 148 |
| Bulk Data Labeling | 134 | 134 |
| OCR / Document Parsing | 95 | 146 |
| Table Extraction from PDFs | 95 | 146 |
| Long-Document Summarization | 146 | 159 |
| Short-Form Summarization | 130 | 131 |
| Blog Post Writing | 133 | 139 |
Scores reflect capability match + benchmark data + pricing for each task. Methodology →
Related comparisons
Qwen: Qwen3.8 27B vs Ling-3.0-flash
Qwen: Qwen3.8 27B vs Google: Gemini 3.6 Flash
Google: Gemini 3.7 Flash vs Ling-3.0-flash
Google: Gemini 3.7 Flash vs Google: Gemini 3.6 Flash
Google: Gemini 3.7 Flash (batch) vs Ling-3.0-flash
Google: Gemini 3.7 Flash (batch) vs Google: Gemini 3.6 Flash
ByteDance Seed: Seed 2.1 Turbo vs Ling-3.0-flash
ByteDance Seed: Seed 2.1 Turbo vs Google: Gemini 3.6 Flash