OpenAI: GPT-6 Luna vs OpenAI: GPT-6 Luna (batch)
Side-by-side comparison of specs, pricing, benchmark scores, and task rankings. Updated 2026-10-04.
| OpenAI: GPT-6 Luna | OpenAI: GPT-6 Luna (batch) | |
|---|---|---|
| Vendor | openai | openai |
| Quality Score | 100 | 100 |
| Benchmark Score | 63.8 | 63.8 |
| Input Price | $0.10/M | $0.05/M |
| Output Price | $0.50/M | $0.25/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 | 62.9 | 62.9 |
The verdict
For a sample job of 1 million input tokens and 250,000 output tokens, GPT-6 Luna (batch) costs $0.11 and GPT-6 Luna costs $0.23, so GPT-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 4 tasks where they differ, GPT-6 Luna (batch) on 4 (Code Completion, Code Documentation, Bulk Data Labeling and others).
Pick GPT-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-6 Luna | OpenAI: GPT-6 Luna (batch) |
|---|---|---|
| Code Completion | 133 | 133 |
| Code Documentation | 137 | 137 |
| Bulk Data Labeling | 129 | 129 |
| Short-Form Summarization | 127 | 127 |
Scores reflect capability match + benchmark data + pricing for each task. Methodology →