# test-dsf-novita-dedicated-pool Usage, Cost & Rank | OpenCode Data

> test-dsf-novita-dedicated-pool ranked #58 by tokens across OpenCode last week, with 0% of tokens over the past two months.

- Page: https://opencode.ai/data/deepseek/test-dsf-novita-dedicated-pool
- JSON: https://opencode.ai/data/deepseek/test-dsf-novita-dedicated-pool.json
- Model ID: test-dsf-novita-dedicated-pool
- Lab: DeepSeek
- Updated: 2026-10-27T08:44:43.000Z

## OpenCode usage: past 2 months

| Metric | Value |
| --- | --- |
| Rank by tokens last week | #58 |
| Tokens | 427K |
| Share of all tokens | 0% |
| Change vs previous 2 months | +100% |
| Unique users | 1 |
| Completed sessions | 19 |
| Average tokens per session | 22K |
| Average cost per session | $0.0000 |
| Total spend | $0 |
| Input tokens served from cache | 22.4% |
| Weekly retention | - |

## Daily usage: past 2 months

| Date | Tokens | Unique users | Sessions |
| --- | --- | --- | --- |
| 2026-10-27 | 427K | 1 | 19 |

## Top countries: past 2 months

| Rank | Country | Tokens | Share |
| --- | --- | --- | --- |
| 1 | United States | 0 | 100% |

## Nearby models by tokens last week

| Rank | Model | Lab | Tokens |
| --- | --- | --- | --- |
| 54 | [kimi-preview-1021](https://opencode.ai/data/moonshot/kimi-preview-1021.md) | Moonshot | 97M |
| 55 | [kenari](https://opencode.ai/data/custom/kenari.md) | Custom | 53M |
| 56 | [qwen3.8-flash-next](https://opencode.ai/data/alibaba/qwen3-8-flash-next.md) | Qwen | 13M |
| 57 | [qwen3.8-27b](https://opencode.ai/data/alibaba/qwen3-8-27b.md) | Qwen | 669K |
| 58 | [test-dsf-novita-dedicated-pool](https://opencode.ai/data/deepseek/test-dsf-novita-dedicated-pool.md) | DeepSeek | 427K |
| 59 | [gpt-oss-120b](https://opencode.ai/data/openai/gpt-oss-120b.md) | OpenAI | 163K |
| 60 | [gemini-3.8-flash](https://opencode.ai/data/google/gemini-3-8-flash.md) | Google | 126K |
| 61 | [internlm/agents-a1](https://opencode.ai/data/custom/internlm-agents-a1.md) | Custom | 89K |
| 62 | [laguna-s-2.1](https://opencode.ai/data/poolside/laguna-s-2-1.md) | Poolside | 32K |
| 63 | [nvidia/nemotron-3.5-super-vl](https://opencode.ai/data/nvidia/nvidia-nemotron-3-5-super-vl.md) | NVIDIA | 7.8K |

## 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.