# kenari Usage, Cost & Rank | OpenCode Data

> kenari ranked #54 by tokens across OpenCode last week, with 0% of tokens over the past two months.

- Page: https://opencode.ai/data/custom/kenari
- JSON: https://opencode.ai/data/custom/kenari.json
- Model ID: kenari
- Lab: Custom
- Updated: 2026-10-25T10:30:21.000Z

## OpenCode usage: past 2 months

| Metric | Value |
| --- | --- |
| Rank by tokens last week | #54 |
| Tokens | 37M |
| Share of all tokens | 0% |
| Change vs previous 2 months | +100% |
| Unique users | 1 |
| Completed sessions | 3 |
| Average tokens per session | 12M |
| Average cost per session | $0.0000 |
| Total spend | $0 |
| Input tokens served from cache | 35% |
| Weekly retention | - |

## Daily usage: past 2 months

| Date | Tokens | Unique users | Sessions |
| --- | --- | --- | --- |
| 2026-10-25 | 37M | 1 | 3 |

## Top countries: past 2 months

| Rank | Country | Tokens | Share |
| --- | --- | --- | --- |
| 1 | Indonesia | 0 | 100% |

## Nearby models by tokens last week

| Rank | Model | Lab | Tokens |
| --- | --- | --- | --- |
| 50 | [gpt-5-nano](https://opencode.ai/data/openai/gpt-5-nano.md) | OpenAI | 307M |
| 51 | [qwen3.7-max](https://opencode.ai/data/alibaba/qwen3-7-max.md) | Qwen | 306M |
| 52 | [test](https://opencode.ai/data/deepseek/test.md) | DeepSeek | 141M |
| 53 | [kimi-preview-1021](https://opencode.ai/data/moonshot/kimi-preview-1021.md) | Moonshot | 97M |
| 54 | [kenari](https://opencode.ai/data/custom/kenari.md) | Custom | 37M |
| 55 | [qwen3.8-flash-next](https://opencode.ai/data/alibaba/qwen3-8-flash-next.md) | Qwen | 10M |
| 56 | [qwen3.8-27b](https://opencode.ai/data/alibaba/qwen3-8-27b.md) | Qwen | 669K |
| 57 | [gemini-3.8-flash](https://opencode.ai/data/google/gemini-3-8-flash.md) | Google | 200K |
| 58 | [internlm/agents-a1](https://opencode.ai/data/custom/internlm-agents-a1.md) | Custom | 89K |
| 59 | [deepseek/deepseek-v4.1-flash](https://opencode.ai/data/deepseek/deepseek-deepseek-v4-1-flash.md) | DeepSeek | 64K |

## 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.