inclusionAI: Ling 3.0 Flash vs OpenAI: GPT-5.6 Luna
Side-by-side comparison of specs, pricing, benchmark scores, and task rankings. Updated 2026-10-02.
| inclusionAI: Ling 3.0 Flash | OpenAI: GPT-5.6 Luna | |
|---|---|---|
| Vendor | inclusionai | openai |
| Quality Score | 100 | 100 |
| Benchmark Score | 30.4 | 62.3 |
| Input Price | $0.02/M | $0.20/M |
| Output Price | $0.06/M | $1.20/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 | 33.2 | 61.6 |
The verdict
For a sample job of 1 million input tokens and 250,000 output tokens, Ling 3.0 Flash costs $0.037 and GPT-5.6 Luna costs $0.50, so Ling 3.0 Flash is about 13.6 times cheaper for the same work.
GPT-5.6 Luna reads up to 1,050,000 tokens at once, roughly 1,575 pages of text, against about 393 pages for Ling 3.0 Flash.
Only GPT-5.6 Luna offers image input.
On our blended benchmark score GPT-5.6 Luna leads 62.3 to 30.4.
Across the 20 tasks where they differ, Ling 3.0 Flash scores higher on 2 (JSON Extraction, Bulk Data Labeling), GPT-5.6 Luna on 18 (SQL Generation, Code Review, Code Completion and others).
Pick Ling 3.0 Flash if you need lower cost; pick GPT-5.6 Luna if you need long documents, image input, benchmark performance or the stronger all-round task scores.
Costs use current list prices per million tokens; page counts assume about 0.75 words per token and 500 words per page.
Who wins by task?
| Task | inclusionAI: Ling 3.0 Flash | OpenAI: GPT-5.6 Luna |
|---|---|---|
| SQL Generation | 135 | 141 |
| Code Review | 132 | 143 |
| Code Completion | 129 | 133 |
| Code Refactoring | 133 | 145 |
| Bug Fixing | 136 | 147 |
| Unit Test Generation | 125 | 131 |
| Code Documentation | 129 | 137 |
| Regex Writing | 123 | 125 |
| CI/CD Pipelines | 121 | 127 |
| Frontend Component Design | 96 | 129 |
| Data Analysis | 129 | 133 |
| CSV / Spreadsheet Cleanup | 129 | 136 |
| ETL Scripting | 127 | 136 |
| JSON Extraction | 132 | 131 |
| Bulk Data Labeling | 130 | 129 |
| OCR / Document Parsing | 84 | 134 |
| Table Extraction from PDFs | 84 | 134 |
| Long-Document Summarization | 135 | 147 |
| Short-Form Summarization | 125 | 126 |
| Blog Post Writing | 123 | 129 |
Scores reflect capability match + benchmark data + pricing for each task. Methodology →