head-to-head
Ling-3.0-flash vs OpenAI: GPT-5.6 Terra Pro
Side-by-side comparison of specs, pricing, benchmark scores, and task rankings. Updated 2026-08-18.
| Ling-3.0-flash | OpenAI: GPT-5.6 Terra Pro | |
|---|---|---|
| Vendor | inclusionai | openai |
| Quality Score | 100 | 100 |
| Benchmark Score | 64.4 | - |
| Input Price | $0.02/M | $2.00/M |
| Output Price | $0.06/M | $12.00/M |
| Context Window | 262,144 | 1,050,000 |
| Max Output | 32,768 | 128,000 |
| Tool Calling | ✓ | ✓ |
| Structured Output | ✓ | ✓ |
| Reasoning Mode | ✓ | ✓ |
| Vision | - | ✓ |
| Audio | - | - |
| Benchmark Scores | ||
| ai_index | 62.4 | - |
| ai_index_agentic | 48.4 | - |
| ai_index_coding | 83.6 | - |
Who wins by task?
| Task | Ling-3.0-flash | OpenAI: GPT-5.6 Terra Pro |
|---|---|---|
| SQL Generation | 159 | 132 |
| Code Review | 152 | 132 |
| Code Completion | 130 | 117 |
| Code Refactoring | 148 | 136 |
| Bug Fixing | 162 | 136 |
| Unit Test Generation | 144 | 124 |
| Code Documentation | 135 | 129 |
| Regex Writing | 132 | 117 |
| CI/CD Pipelines | 135 | 120 |
| Frontend Component Design | 110 | 122 |
| Data Analysis | 158 | 124 |
| CSV / Spreadsheet Cleanup | 145 | 132 |
| ETL Scripting | 142 | 128 |
| JSON Extraction | 146 | 121 |
| Bulk Data Labeling | 134 | 117 |
| OCR / Document Parsing | 95 | 131 |
| Table Extraction from PDFs | 95 | 131 |
| Long-Document Summarization | 146 | 136 |
| Short-Form Summarization | 130 | 113 |
| Blog Post Writing | 133 | 120 |
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 OpenAI: GPT-5.6 Terra Pro
Google: Gemini 3.7 Flash vs Ling-3.0-flash
Google: Gemini 3.7 Flash vs OpenAI: GPT-5.6 Terra Pro
Google: Gemini 3.7 Flash (batch) vs Ling-3.0-flash
Google: Gemini 3.7 Flash (batch) vs OpenAI: GPT-5.6 Terra Pro
ByteDance Seed: Seed 2.1 Turbo vs Ling-3.0-flash
ByteDance Seed: Seed 2.1 Turbo vs OpenAI: GPT-5.6 Terra Pro