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

> ll-alpha ranked #29 by tokens across OpenCode last week, with 0.0% of tokens over the past two months.

- Page: https://opencode.ai/data/unknown/ll-alpha
- JSON: https://opencode.ai/data/unknown/ll-alpha.json
- Model ID: ll-alpha
- Lab: Unknown
- Updated: 2026-10-16T20:32:02.000Z

## OpenCode usage: past 2 months

| Metric | Value |
| --- | --- |
| Rank by tokens last week | #29 |
| Tokens | 55B |
| Share of all tokens | 0.0% |
| Change vs previous 2 months | +100% |
| Unique users | 3.2K |
| Completed sessions | 64,353 |
| Average tokens per session | 861K |
| Average cost per session | $0.0000 |
| Total spend | $0 |
| Input tokens served from cache | 89.7% |
| Weekly retention | - |

## Daily usage: past 2 months

| Date | Tokens | Unique users | Sessions |
| --- | --- | --- | --- |
| 2026-10-16 | 55B | 3.2K | 64,353 |

## Top countries: past 2 months

| Rank | Country | Tokens | Share |
| --- | --- | --- | --- |
| 1 | India | 7B | 12.7% |
| 2 | United States | 3.6B | 6.5% |
| 3 | China | 3.3B | 6% |
| 4 | Germany | 2.8B | 5.1% |
| 5 | Brazil | 2.6B | 4.7% |
| 6 | Indonesia | 2.3B | 4.2% |
| 7 | Spain | 1.9B | 3.4% |
| 8 | France | 1.7B | 3% |
| 9 | Russia | 1.6B | 2.9% |
| 10 | Netherlands | 1.3B | 2.4% |
| 11 | United Kingdom | 1.2B | 2.2% |
| 12 | Türkiye | 1.1B | 1.9% |
| 13 | Italy | 1B | 1.9% |
| 14 | Philippines | 900M | 1.7% |
| 15 | Pakistan | 900M | 1.7% |

## Nearby models by tokens last week

| Rank | Model | Lab | Tokens |
| --- | --- | --- | --- |
| 25 | [ling-3.1-flash](https://opencode.ai/data/inclusionai/ling-3-1-flash.md) | inclusionAI | 93B |
| 26 | [gemini-4-argon-contributor](https://opencode.ai/data/google/gemini-4-argon-contributor.md) | Google | 73B |
| 27 | [qwen3.7-plus](https://opencode.ai/data/alibaba/qwen3-7-plus.md) | Qwen | 64B |
| 28 | [glm-5.2](https://opencode.ai/data/zhipuai/glm-5-2.md) | Zhipu | 57B |
| 29 | [ll-alpha](https://opencode.ai/data/unknown/ll-alpha.md) | - | 55B |
| 30 | [kimi-k3](https://opencode.ai/data/moonshotai/kimi-k3.md) | Moonshot | 47B |
| 31 | [mimo-v2.5-pro](https://opencode.ai/data/xiaomi/mimo-v2-5-pro.md) | Xiaomi | 36B |
| 32 | [longcat-2.0](https://opencode.ai/data/meituan/longcat-2-0.md) | Meituan | 29B |
| 33 | [jev-1.13](https://opencode.ai/data/unknown/jev-1-13.md) | - | 25B |
| 34 | [qwen3.8-max](https://opencode.ai/data/alibaba/qwen3-8-max.md) | Qwen | 17B |

## 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.