Xiaomi: MiMo-V2.6-Pro-UltraSpeed vs DeepSeek: DeepSeek V4 Flash Vision Exp
Side-by-side comparison of specs, pricing, benchmark scores, and task rankings. Updated 2026-11-07.
| Xiaomi: MiMo-V2.6-Pro-UltraSpeed | DeepSeek: DeepSeek V4 Flash Vision Exp | |
|---|---|---|
| Vendor | xiaomi | deepseek |
| Quality Score | 100 | 100 |
| Input Price | $4.35/M | $0.44/M |
| Output Price | $8.70/M | $1.32/M |
| Context Window | 1,048,576 | 1,048,576 |
| Max Output | 131,072 | 943,717 |
| Tool Calling | ✓ | ✓ |
| Structured Output | ✓ | ✓ |
| Reasoning Mode | ✓ | ✓ |
| Vision | ✓ | ✓ |
| Audio | ✓ | - |
The verdict
For a sample job of 1 million input tokens and 250,000 output tokens, DeepSeek V4 Flash Vision Exp costs $0.77 and MiMo-V2.6-Pro-UltraSpeed costs $6.52, so DeepSeek V4 Flash Vision Exp is about 8.5 times cheaper for the same work.
Both read up to 1,048,576 tokens at once, roughly 1,573 pages of text.
Only MiMo-V2.6-Pro-UltraSpeed offers audio input and video input.
Across the 10 tasks where they differ, DeepSeek V4 Flash Vision Exp on 10 (SQL Generation, Code Completion, Code Documentation and others).
MiMo-V2.6-Pro-UltraSpeed was released in September 2026 and DeepSeek V4 Flash Vision Exp in August 2026.
Pick MiMo-V2.6-Pro-UltraSpeed if you need audio input or video input; pick DeepSeek V4 Flash Vision Exp 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 | Xiaomi: MiMo-V2.6-Pro-UltraSpeed | DeepSeek: DeepSeek V4 Flash Vision Exp |
|---|---|---|
| SQL Generation | 132 | 133 |
| Code Completion | 117 | 131 |
| Code Documentation | 129 | 131 |
| Regex Writing | 117 | 119 |
| CSV / Spreadsheet Cleanup | 132 | 133 |
| JSON Extraction | 121 | 131 |
| Bulk Data Labeling | 118 | 129 |
| Long-Document Summarization | 136 | 137 |
| Short-Form Summarization | 113 | 123 |
| Blog Post Writing | 120 | 121 |
Scores reflect capability match + benchmark data + pricing for each task. Methodology →