head-to-head
OpenAI: GPT-5.6 Luna (batch) vs Anthropic: Claude Opus 4.8 (batch)
Side-by-side comparison of specs, pricing, benchmark scores, and task rankings. Updated 2026-08-13.
| OpenAI: GPT-5.6 Luna (batch) | Anthropic: Claude Opus 4.8 (batch) | |
|---|---|---|
| Vendor | openai | anthropic |
| Quality Score | 100 | 100 |
| Benchmark Score | 88.2 | 94.7 |
| Input Price | $0.10/M | $2.50/M |
| Output Price | $0.60/M | $12.50/M |
| Context Window | 1,050,000 | 1,000,000 |
| Max Output | 128,000 | 128,000 |
| Tool Calling | ✓ | ✓ |
| Structured Output | ✓ | ✓ |
| Reasoning Mode | ✓ | ✓ |
| Vision | ✓ | ✓ |
| Audio | - | - |
| Benchmark Scores | ||
| ai_index | 86.3 | 94.6 |
| ai_index_agentic | 77.4 | 81.5 |
| ai_index_coding | 100.0 | 100.0 |
| eqbench | - | 83.3 |
Who wins by task?
| Task | OpenAI: GPT-5.6 Luna (batch) | Anthropic: Claude Opus 4.8 (batch) |
|---|---|---|
| SQL Generation | 172 | 178 |
| Code Review | 167 | 179 |
| Code Completion | 133 | 121 |
| Code Refactoring | 164 | 176 |
| Bug Fixing | 180 | 193 |
| Unit Test Generation | 154 | 161 |
| Code Documentation | 143 | 148 |
| Regex Writing | 137 | 138 |
| CI/CD Pipelines | 144 | 151 |
| Frontend Component Design | 146 | 151 |
| Data Analysis | 171 | 178 |
| CSV / Spreadsheet Cleanup | 154 | 158 |
| ETL Scripting | 154 | 164 |
| JSON Extraction | 149 | 138 |
| Bulk Data Labeling | 135 | 123 |
| OCR / Document Parsing | 146 | 149 |
| Table Extraction from PDFs | 146 | 149 |
| Long-Document Summarization | 160 | 171 |
| Short-Form Summarization | 132 | 123 |
| Blog Post Writing | 140 | 146 |
Scores reflect capability match + benchmark data + pricing for each task. Methodology →
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