OpenAI: GPT-5.6 Luna vs OpenAI: GPT-5.6 Luna (batch)
Side-by-side comparison of specs, pricing, benchmark scores, and task rankings. Updated 2026-11-07.
| OpenAI: GPT-5.6 Luna | OpenAI: GPT-5.6 Luna (batch) | |
|---|---|---|
| Vendor | openai | openai |
| Quality Score | 100 | 100 |
| Benchmark Score | 89.4 | 89.4 |
| Input Price | $0.20/M | $0.10/M |
| Output Price | $1.20/M | $0.60/M |
| Context Window | 1,050,000 | 1,050,000 |
| Max Output | 128,000 | 128,000 |
| Tool Calling | ✓ | ✓ |
| Structured Output | ✓ | ✓ |
| Reasoning Mode | ✓ | ✓ |
| Vision | ✓ | ✓ |
| Audio | - | - |
| Benchmark Scores | ||
| ai_index | 84.5 | 84.5 |
| ai_index_agentic | 75.2 | 75.2 |
| ai_index_coding | 100.0 | 100.0 |
The verdict
For a sample job of 1 million input tokens and 250,000 output tokens, GPT-5.6 Luna (batch) costs $0.25 and GPT-5.6 Luna costs $0.50, so GPT-5.6 Luna (batch) is about 2.0 times cheaper for the same work.
Both read up to 1,050,000 tokens at once, roughly 1,575 pages of text.
Across the 10 tasks where they differ, GPT-5.6 Luna (batch) on 10 (SQL Generation, Code Completion, Code Documentation and others).
Pick GPT-5.6 Luna (batch) if you need lower cost or the stronger all-round task scores.
Costs use current list prices per million tokens; page counts assume about 0.75 words per token and 500 words per page.
Who wins by task?
| Task | OpenAI: GPT-5.6 Luna | OpenAI: GPT-5.6 Luna (batch) |
|---|---|---|
| SQL Generation | 171 | 171 |
| Code Completion | 133 | 133 |
| Code Documentation | 143 | 143 |
| Regex Writing | 136 | 136 |
| CSV / Spreadsheet Cleanup | 154 | 154 |
| JSON Extraction | 149 | 149 |
| Bulk Data Labeling | 135 | 135 |
| Long-Document Summarization | 159 | 160 |
| Short-Form Summarization | 132 | 132 |
| Blog Post Writing | 140 | 140 |
Scores reflect capability match + benchmark data + pricing for each task. Methodology →