# DeepSeek V4 Flash vs Nemotron 3.5 Super 120B A12B - AI Model Comparison

- Page: https://opencode.ai/data/compare/deepseek/deepseek-v4-flash/nvidia/nemotron-3-5-super-120b-a12b
- Updated: 2026-10-21T06:53:33.000Z

|  | DeepSeek V4 Flash | Nemotron 3.5 Super 120B A12B |
| --- | --- | --- |
| Lab | DeepSeek | NVIDIA |
| Context window | 1M | 1M |
| Max output | 384K | 131K |
| Input modalities | text | text |
| Reasoning | Yes | Yes |
| Tool calling | Yes | Yes |
| Open weights | Yes | Yes |
| Release date | 2026-04-24 | 2026-10-15 |
| Input price per 1M tokens | $0.39 | - |
| Output price per 1M tokens | $1.56 | - |
| Cached input price per 1M tokens | $0.0078 | - |
| OpenCode tokens: past 2 months | 107T | - |
| Share of all tokens | 10% | - |
| Rank by tokens last week | #10 | - |
| Unique users | 2.2M | - |
| Weekly retention | 67.1% | - |

Model pages: [DeepSeek V4 Flash](https://opencode.ai/data/deepseek/deepseek-v4-flash.md), [Nemotron 3.5 Super 120B A12B](https://opencode.ai/data/nvidia/nemotron-3-5-super-120b-a12b.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.