head-to-head
OpenAI: GPT-5.6 Sol Pro (batch) vs Google: Gemini 3.5 Flash
Side-by-side comparison of specs, pricing, benchmark scores, and task rankings. Updated 2026-09-23.
| OpenAI: GPT-5.6 Sol Pro (batch) | Google: Gemini 3.5 Flash | |
|---|---|---|
| Vendor | openai | |
| Quality Score | 100 | 100 |
| Benchmark Score | - | 53.5 |
| Input Price | $1.00/M | $1.50/M |
| Output Price | $5.00/M | $9.00/M |
| Context Window | 1,050,000 | 1,048,576 |
| Max Output | 128,000 | 65,536 |
| Tool Calling | ✓ | ✓ |
| Structured Output | ✓ | ✓ |
| Reasoning Mode | ✓ | ✓ |
| Vision | ✓ | ✓ |
| Audio | - | ✓ |
| Benchmark Scores | ||
| ai_index | - | 53.8 |
Who wins by task?
| Task | OpenAI: GPT-5.6 Sol Pro (batch) | Google: Gemini 3.5 Flash |
|---|---|---|
| SQL Generation | 133 | 139 |
| Code Review | 132 | 142 |
| Code Completion | 118 | 119 |
| Code Refactoring | 136 | 144 |
| Bug Fixing | 136 | 146 |
| Unit Test Generation | 124 | 130 |
| Code Documentation | 130 | 134 |
| Regex Writing | 118 | 123 |
| CI/CD Pipelines | 120 | 126 |
| Frontend Component Design | 122 | 128 |
| Data Analysis | 124 | 132 |
| CSV / Spreadsheet Cleanup | 133 | 135 |
| ETL Scripting | 128 | 135 |
| JSON Extraction | 122 | 121 |
| Bulk Data Labeling | 120 | 118 |
| OCR / Document Parsing | 131 | 133 |
| Table Extraction from PDFs | 131 | 133 |
| Long-Document Summarization | 137 | 145 |
| Short-Form Summarization | 114 | 116 |
| Blog Post Writing | 121 | 127 |
Scores reflect capability match + benchmark data + pricing for each task. Methodology →
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