head-to-head
Meta: Muse Spark 1.1 vs OpenAI: GPT-5.6 Luna (batch)
Side-by-side comparison of specs, pricing, benchmark scores, and task rankings. Updated 2026-08-13.
| Meta: Muse Spark 1.1 | OpenAI: GPT-5.6 Luna (batch) | |
|---|---|---|
| Vendor | meta | openai |
| Quality Score | 100 | 100 |
| Benchmark Score | 85.2 | 88.2 |
| Input Price | $1.25/M | $0.10/M |
| Output Price | $4.25/M | $0.60/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 | 87.8 | 86.3 |
| ai_index_agentic | 65.6 | 77.4 |
| ai_index_coding | 100.0 | 100.0 |
Who wins by task?
| Task | Meta: Muse Spark 1.1 | OpenAI: GPT-5.6 Luna (batch) |
|---|---|---|
| SQL Generation | 170 | 172 |
| Code Review | 166 | 167 |
| Code Completion | 120 | 133 |
| Code Refactoring | 163 | 164 |
| Bug Fixing | 178 | 180 |
| Unit Test Generation | 153 | 154 |
| Code Documentation | 142 | 143 |
| Regex Writing | 135 | 137 |
| CI/CD Pipelines | 144 | 144 |
| Frontend Component Design | 146 | 146 |
| Data Analysis | 168 | 171 |
| CSV / Spreadsheet Cleanup | 153 | 154 |
| ETL Scripting | 153 | 154 |
| JSON Extraction | 139 | 149 |
| Bulk Data Labeling | 126 | 135 |
| OCR / Document Parsing | 146 | 146 |
| Table Extraction from PDFs | 146 | 146 |
| Long-Document Summarization | 159 | 160 |
| Short-Form Summarization | 123 | 132 |
| Blog Post Writing | 139 | 140 |
Scores reflect capability match + benchmark data + pricing for each task. Methodology →
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