OpenAI: GPT-6 Luna vs Xiaomi: MiMo-V2.6-Flash
Side-by-side comparison of specs, pricing, benchmark scores, and task rankings. Updated 2026-10-04.
| OpenAI: GPT-6 Luna | Xiaomi: MiMo-V2.6-Flash | |
|---|---|---|
| Vendor | openai | xiaomi |
| Quality Score | 100 | 100 |
| Benchmark Score | 63.8 | 63.3 |
| Input Price | $0.10/M | $0.14/M |
| Output Price | $0.50/M | $0.28/M |
| Context Window | 1,050,000 | 1,050,000 |
| Max Output | 128,000 | 131,072 |
| Tool Calling | ✓ | ✓ |
| Structured Output | ✓ | ✓ |
| Reasoning Mode | ✓ | ✓ |
| Vision | ✓ | ✓ |
| Audio | - | ✓ |
| Benchmark Scores | ||
| ai_index | 62.9 | 62.5 |
The verdict
For a sample job of 1 million input tokens and 250,000 output tokens, MiMo-V2.6-Flash costs $0.21 and GPT-6 Luna costs $0.23, so MiMo-V2.6-Flash is slightly cheaper for the same work.
Both read up to 1,050,000 tokens at once, roughly 1,575 pages of text.
Only MiMo-V2.6-Flash offers audio input and video input.
Across the 5 tasks where they differ, GPT-6 Luna scores higher on 3 (Code Review, Code Refactoring, Bug Fixing), MiMo-V2.6-Flash on 2 (Code Completion, Bulk Data Labeling).
Pick MiMo-V2.6-Flash if you need lower cost, audio input or video input.
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 | Xiaomi: MiMo-V2.6-Flash |
|---|---|---|
| Code Review | 144 | 143 |
| Code Completion | 133 | 133 |
| Code Refactoring | 146 | 146 |
| Bug Fixing | 148 | 147 |
| Bulk Data Labeling | 129 | 129 |
Scores reflect capability match + benchmark data + pricing for each task. Methodology →