head-to-head
Meta: Muse Spark 1.1 vs OpenAI: GPT-5.6 Luna
Side-by-side comparison of specs, pricing, benchmark scores, and task rankings. Updated 2026-07-18.
| Meta: Muse Spark 1.1 | OpenAI: GPT-5.6 Luna | |
|---|---|---|
| Vendor | meta | openai |
| Quality Score | 100 | 100 |
| Benchmark Score | - | 89.4 |
| Input Price | $1.25/M | $1.00/M |
| Output Price | $4.25/M | $6.00/M |
| Context Window | 1,048,576 | 1,050,000 |
| Max Output | - | 128,000 |
| Tool Calling | ✓ | ✓ |
| Structured Output | ✓ | ✓ |
| Reasoning Mode | ✓ | ✓ |
| Vision | ✓ | ✓ |
| Audio | ✓ | - |
| Benchmark Scores | ||
| ai_index | - | 84.5 |
| ai_index_agentic | - | 75.2 |
| ai_index_coding | - | 100.0 |
Who wins by task?
| Task | Meta: Muse Spark 1.1 | OpenAI: GPT-5.6 Luna |
|---|---|---|
| SQL Generation | 133 | 171 |
| Code Review | 132 | 166 |
| Code Completion | 118 | 120 |
| Code Refactoring | 136 | 163 |
| Bug Fixing | 136 | 179 |
| Unit Test Generation | 124 | 154 |
| Code Documentation | 130 | 142 |
| Regex Writing | 118 | 135 |
| CI/CD Pipelines | 120 | 144 |
| Frontend Component Design | 122 | 146 |
| Data Analysis | 124 | 170 |
| CSV / Spreadsheet Cleanup | 133 | 153 |
| ETL Scripting | 128 | 154 |
| JSON Extraction | 122 | 139 |
| Bulk Data Labeling | 120 | 125 |
| OCR / Document Parsing | 131 | 146 |
| Table Extraction from PDFs | 131 | 146 |
| Long-Document Summarization | 137 | 159 |
| Short-Form Summarization | 114 | 123 |
| Blog Post Writing | 121 | 140 |
Scores reflect capability match + benchmark data + pricing for each task. Methodology →
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