# DeepSeek V4 Pro vs mai-experimental-test - AI Model Comparison

- Page: https://opencode.ai/data/compare/deepseek/deepseek-v4-pro/unknown/mai-experimental-test
- Updated: 2026-10-02T17:41:52.000Z

|  | DeepSeek V4 Pro | mai-experimental-test |
| --- | --- | --- |
| Lab | DeepSeek | Unknown |
| Context window | 1M | - |
| Max output | 384K | - |
| Input modalities | text | - |
| Reasoning | Yes | - |
| Tool calling | Yes | - |
| Open weights | Yes | - |
| Release date | 2026-04-24 | - |
| Input price per 1M tokens | $1.74 | - |
| Output price per 1M tokens | $3.48 | - |
| Cached input price per 1M tokens | $0.20 | - |
| OpenCode tokens: past 2 months | 17T | 273B |
| Share of all tokens | 1.9% | 0.0% |
| Rank by tokens last week | #13 | #17 |
| Unique users | 963K | 56K |
| Weekly retention | 56.1% | - |

Model pages: [DeepSeek V4 Pro](https://opencode.ai/data/deepseek/deepseek-v4-pro.md), [mai-experimental-test](https://opencode.ai/data/unknown/mai-experimental-test.md)

## Methodology

- Updates: Aggregated every hour. Days and weeks use UTC.
- Tokens: Input, output, reasoning, and cached tokens for each request.
- Users and sessions: Approximate counts of distinct users and OpenCode sessions.
- Cost: Session cost is the average cost per OpenCode session. Token prices are list prices from the OpenCode model catalog.
- Retention: The share of a model's users in one week who use it again the next week.
- Citation: Cite OpenCode Data (opencode.ai/data) with the update time shown at the top of the page.