head-to-head
Meta: Muse Spark 1.1 vs OpenAI: GPT-5.6 Sol (batch)
Side-by-side comparison of specs, pricing, benchmark scores, and task rankings. Updated 2026-09-23.
| Meta: Muse Spark 1.1 | OpenAI: GPT-5.6 Sol (batch) | |
|---|---|---|
| Vendor | meta | openai |
| Quality Score | 100 | 100 |
| Benchmark Score | 55.7 | 80.2 |
| Input Price | $1.25/M | $1.00/M |
| Output Price | $4.25/M | $5.00/M |
| Context Window | 1,048,576 | 1,050,000 |
| Max Output | 943,718 | 128,000 |
| Tool Calling | ✓ | ✓ |
| Structured Output | ✓ | ✓ |
| Reasoning Mode | ✓ | ✓ |
| Vision | ✓ | ✓ |
| Audio | ✓ | - |
| Benchmark Scores | ||
| ai_index | 55.7 | 77.5 |
Who wins by task?
| Task | Meta: Muse Spark 1.1 | OpenAI: GPT-5.6 Sol (batch) |
|---|---|---|
| SQL Generation | 140 | 142 |
| Code Review | 142 | 146 |
| Code Completion | 120 | 120 |
| Code Refactoring | 144 | 148 |
| Bug Fixing | 146 | 150 |
| Unit Test Generation | 130 | 133 |
| Code Documentation | 135 | 137 |
| Regex Writing | 124 | 126 |
| CI/CD Pipelines | 126 | 129 |
| Frontend Component Design | 128 | 131 |
| Data Analysis | 132 | 135 |
| CSV / Spreadsheet Cleanup | 135 | 136 |
| ETL Scripting | 135 | 138 |
| JSON Extraction | 122 | 122 |
| Bulk Data Labeling | 120 | 120 |
| OCR / Document Parsing | 133 | 134 |
| Table Extraction from PDFs | 133 | 134 |
| Long-Document Summarization | 146 | 149 |
| Short-Form Summarization | 117 | 118 |
| Blog Post Writing | 128 | 130 |
Scores reflect capability match + benchmark data + pricing for each task. Methodology →
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