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

> pulse-alpha ranked #34 by tokens across OpenCode last week, with 0% of tokens over the past two months.

- Page: https://opencode.ai/data/unknown/pulse-alpha
- JSON: https://opencode.ai/data/unknown/pulse-alpha.json
- Model ID: pulse-alpha
- Lab: Unknown
- Updated: 2026-11-03T01:20:42.000Z

## OpenCode usage: past 2 months

| Metric | Value |
| --- | --- |
| Rank by tokens last week | #34 |
| Tokens | 12B |
| Share of all tokens | 0% |
| Change vs previous 2 months | +100% |
| Unique users | 570 |
| Completed sessions | 4,394 |
| Average tokens per session | 2.7M |
| Average cost per session | $0.0000 |
| Total spend | $0 |
| Input tokens served from cache | 97.4% |
| Weekly retention | - |

## Daily usage: past 2 months

| Date | Tokens | Unique users | Sessions |
| --- | --- | --- | --- |
| 2026-11-02 | 6.1B | 296 | 2,458 |
| 2026-11-03 | 5.8B | 274 | 1,936 |

## Top countries: past 2 months

| Rank | Country | Tokens | Share |
| --- | --- | --- | --- |
| 1 | United States | 2B | 16.5% |
| 2 | Brazil | 1.5B | 12.4% |
| 3 | Indonesia | 500M | 4.6% |
| 4 | Canada | 500M | 3.9% |
| 5 | Morocco | 500M | 3.8% |
| 6 | China | 400M | 3.6% |
| 7 | Egypt | 400M | 3.6% |
| 8 | United Kingdom | 400M | 3.5% |
| 9 | Türkiye | 300M | 2.9% |
| 10 | Australia | 300M | 2.9% |
| 11 | India | 300M | 2.6% |
| 12 | Mexico | 300M | 2.6% |
| 13 | Argentina | 300M | 2.6% |
| 14 | Colombia | 300M | 2.5% |
| 15 | Pakistan | 200M | 1.8% |

## Nearby models by tokens last week

| Rank | Model | Lab | Tokens |
| --- | --- | --- | --- |
| 30 | [longcat-2.0](https://opencode.ai/data/meituan/longcat-2-0.md) | Meituan | 41B |
| 31 | [kimi-k3](https://opencode.ai/data/moonshotai/kimi-k3.md) | Moonshot | 37B |
| 32 | [qwen3.8-max](https://opencode.ai/data/alibaba/qwen3-8-max.md) | Qwen | 21B |
| 33 | [grok-4.7](https://opencode.ai/data/xai/grok-4-7.md) | xAI | 13B |
| 34 | [pulse-alpha](https://opencode.ai/data/unknown/pulse-alpha.md) | - | 12B |
| 35 | [hy3](https://opencode.ai/data/tencent/hy3.md) | Tencent | 11B |
| 36 | [step-5-preview](https://opencode.ai/data/stepfun/step-5-preview.md) | StepFun | 8.6B |
| 37 | [hy4-preview](https://opencode.ai/data/tencent/hy4-preview.md) | Tencent | 8.2B |
| 38 | [jev-1.13](https://opencode.ai/data/unknown/jev-1-13.md) | - | 4.3B |
| 39 | [omen-alpha](https://opencode.ai/data/unknown/omen-alpha.md) | - | 1.2B |

## 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.