# fledge-alpha Usage, Cost & Rank | OpenCode Data

> fledge-alpha ranked #23 by tokens across OpenCode last week, with 0.0% of tokens over the past two months.

- Page: https://opencode.ai/data/unknown/fledge-alpha
- JSON: https://opencode.ai/data/unknown/fledge-alpha.json
- Model ID: fledge-alpha
- Lab: Unknown
- Updated: 2026-10-02T08:39:37.000Z

## OpenCode usage: past 2 months

| Metric | Value |
| --- | --- |
| Rank by tokens last week | #23 |
| Tokens | 90B |
| Share of all tokens | 0.0% |
| Change vs previous 2 months | +100% |
| Unique users | 2K |
| Completed sessions | 60,263 |
| Average tokens per session | 1.5M |
| Average cost per session | $0.0000 |
| Total spend | $0 |
| Input tokens served from cache | 93.3% |
| Weekly retention | - |

## Daily usage: past 2 months

| Date | Tokens | Unique users | Sessions |
| --- | --- | --- | --- |
| 2026-09-30 | 861K | 1 | 4 |
| 2026-10-01 | 29B | 782 | 23,080 |
| 2026-10-02 | 62B | 1.2K | 37,179 |

## Top countries: past 2 months

| Rank | Country | Tokens | Share |
| --- | --- | --- | --- |
| 1 | United States | 17B | 18.8% |
| 2 | India | 8.5B | 9.4% |
| 3 | Brazil | 6.4B | 7.1% |
| 4 | Indonesia | 5.3B | 5.9% |
| 5 | China | 4.8B | 5.3% |
| 6 | Mexico | 2.8B | 3.1% |
| 7 | Colombia | 2.6B | 2.9% |
| 8 | United Kingdom | 2.5B | 2.7% |
| 9 | Canada | 2.4B | 2.7% |
| 10 | Argentina | 2.2B | 2.4% |
| 11 | Türkiye | 2B | 2.2% |
| 12 | Philippines | 1.9B | 2.1% |
| 13 | Singapore | 1.8B | 2% |
| 14 | Japan | 1.8B | 2% |
| 15 | Vietnam | 1.6B | 1.8% |

## Nearby models by tokens last week

| Rank | Model | Lab | Tokens |
| --- | --- | --- | --- |
| 19 | [minimax-m3](https://opencode.ai/data/minimax/minimax-m3.md) | MiniMax | 181B |
| 20 | [mai-experimental-test](https://opencode.ai/data/unknown/mai-experimental-test.md) | - | 180B |
| 21 | [kimi-k2.7-code](https://opencode.ai/data/moonshotai/kimi-k2-7-code.md) | Moonshot | 136B |
| 22 | [glm-5.3](https://opencode.ai/data/zhipuai/glm-5-3.md) | Zhipu | 95B |
| 23 | [fledge-alpha](https://opencode.ai/data/unknown/fledge-alpha.md) | - | 90B |
| 24 | [qwen3.7-plus](https://opencode.ai/data/alibaba/qwen3-7-plus.md) | Qwen | 76B |
| 25 | [glm-5.2](https://opencode.ai/data/zhipuai/glm-5-2.md) | Zhipu | 61B |
| 26 | [kimi-k3](https://opencode.ai/data/moonshotai/kimi-k3.md) | Moonshot | 45B |
| 27 | [mimo-v2.5-pro](https://opencode.ai/data/xiaomi/mimo-v2-5-pro.md) | Xiaomi | 42B |
| 28 | [longcat-2.0](https://opencode.ai/data/meituan/longcat-2-0.md) | Meituan | 26B |

## 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.