head-to-head
OpenAI: GPT-6 Sol (batch) vs Meta: Muse Spark 1.3
Side-by-side comparison of specs, pricing, benchmark scores, and task rankings. Updated 2026-09-23.
| OpenAI: GPT-6 Sol (batch) | Meta: Muse Spark 1.3 | |
|---|---|---|
| Vendor | openai | meta |
| Quality Score | 100 | 100 |
| Benchmark Score | 81.2 | 82.3 |
| Input Price | $1.00/M | $1.25/M |
| Output Price | $5.00/M | $4.25/M |
| Context Window | 1,050,000 | 1,048,576 |
| Max Output | 128,000 | 943,718 |
| Tool Calling | ✓ | ✓ |
| Structured Output | ✓ | ✓ |
| Reasoning Mode | ✓ | ✓ |
| Vision | ✓ | ✓ |
| Audio | - | ✓ |
| Benchmark Scores | ||
| ai_index | 78.4 | 79.4 |
Who wins by task?
| Task | OpenAI: GPT-6 Sol (batch) | Meta: Muse Spark 1.3 |
|---|---|---|
| SQL Generation | 142 | 143 |
| Code Review | 146 | 147 |
| Code Completion | 120 | 120 |
| Code Refactoring | 148 | 148 |
| Bug Fixing | 150 | 151 |
| Unit Test Generation | 133 | 133 |
| Code Documentation | 137 | 138 |
| Regex Writing | 126 | 126 |
| CI/CD Pipelines | 129 | 129 |
| Frontend Component Design | 131 | 131 |
| Data Analysis | 135 | 135 |
| CSV / Spreadsheet Cleanup | 136 | 136 |
| ETL Scripting | 139 | 139 |
| JSON Extraction | 122 | 122 |
| Bulk Data Labeling | 120 | 120 |
| OCR / Document Parsing | 134 | 135 |
| Table Extraction from PDFs | 134 | 135 |
| Long-Document Summarization | 149 | 150 |
| Short-Form Summarization | 118 | 118 |
| Blog Post Writing | 130 | 131 |
Scores reflect capability match + benchmark data + pricing for each task. Methodology →
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