OpenAI: GPT-6.1 Sol Pro (batch) vs OpenAI: GPT-6.1 Sol (batch)
Side-by-side comparison of specs, pricing, benchmark scores, and task rankings. Updated 2026-09-30.
| OpenAI: GPT-6.1 Sol Pro (batch) | OpenAI: GPT-6.1 Sol (batch) | |
|---|---|---|
| Vendor | openai | openai |
| Quality Score | 100 | 100 |
| Benchmark Score | - | 89.2 |
| Input Price | $1.00/M | $1.00/M |
| Output Price | $5.00/M | $5.00/M |
| Context Window | 1,050,000 | 1,050,000 |
| Max Output | 128,000 | 128,000 |
| Tool Calling | ✓ | ✓ |
| Structured Output | ✓ | ✓ |
| Reasoning Mode | ✓ | ✓ |
| Vision | ✓ | ✓ |
| Audio | - | - |
| Benchmark Scores | ||
| ai_index | - | 85.5 |
The verdict
For a sample job of 1 million input tokens and 250,000 output tokens, both cost $2.25 at current list prices.
Both read up to 1,050,000 tokens at once, roughly 1,575 pages of text.
Across the 18 tasks where they differ, GPT-6.1 Sol (batch) on 18 (SQL Generation, Code Review, Code Completion and others).
Pick GPT-6.1 Sol (batch) if you need 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 | OpenAI: GPT-6.1 Sol Pro (batch) | OpenAI: GPT-6.1 Sol (batch) |
|---|---|---|
| SQL Generation | 133 | 143 |
| Code Review | 132 | 148 |
| Code Completion | 118 | 120 |
| Code Refactoring | 136 | 149 |
| Bug Fixing | 136 | 152 |
| Unit Test Generation | 124 | 134 |
| Code Documentation | 130 | 138 |
| Regex Writing | 118 | 127 |
| CI/CD Pipelines | 120 | 130 |
| Frontend Component Design | 122 | 132 |
| Data Analysis | 124 | 136 |
| CSV / Spreadsheet Cleanup | 133 | 136 |
| ETL Scripting | 128 | 140 |
| OCR / Document Parsing | 131 | 135 |
| Table Extraction from PDFs | 131 | 135 |
| Long-Document Summarization | 137 | 151 |
| Short-Form Summarization | 114 | 119 |
| Blog Post Writing | 121 | 131 |
Scores reflect capability match + benchmark data + pricing for each task. Methodology →