# iceman-contributor Usage, Cost & Rank | OpenCode Data

> iceman-contributor ranked #43 by tokens across OpenCode last week, with 0% of tokens over the past two months.

- Page: https://opencode.ai/data/unknown/iceman-contributor
- JSON: https://opencode.ai/data/unknown/iceman-contributor.json
- Model ID: iceman-contributor
- Lab: Unknown
- Updated: 2026-10-25T08:33:15.000Z

## OpenCode usage: past 2 months

| Metric | Value |
| --- | --- |
| Rank by tokens last week | #43 |
| Tokens | 5.1B |
| Share of all tokens | 0% |
| Change vs previous 2 months | +100% |
| Unique users | 1.2K |
| Completed sessions | 10,914 |
| Average tokens per session | 465K |
| Average cost per session | $0.0000 |
| Total spend | $0 |
| Input tokens served from cache | 88.6% |
| Weekly retention | - |

## Daily usage: past 2 months

| Date | Tokens | Unique users | Sessions |
| --- | --- | --- | --- |
| 2026-10-24 | 809M | 359 | 2,562 |
| 2026-10-25 | 4.3B | 844 | 8,352 |

## Top countries: past 2 months

| Rank | Country | Tokens | Share |
| --- | --- | --- | --- |
| 1 | United States | 900M | 18.1% |
| 2 | Germany | 700M | 14.4% |
| 3 | China | 400M | 7.8% |
| 4 | United Kingdom | 400M | 7.5% |
| 5 | Canada | 300M | 6.4% |
| 6 | India | 300M | 6.3% |
| 7 | Brazil | 300M | 5.5% |
| 8 | Vietnam | 200M | 4.3% |
| 9 | South Africa | 200M | 4.1% |
| 10 | Japan | 200M | 3.2% |
| 11 | Australia | 100M | 2.1% |
| 12 | Algeria | 100M | 2% |
| 13 | France | 100M | 1.5% |
| 14 | Singapore | 100M | 1.4% |
| 15 | Egypt | 100M | 1.2% |

## Nearby models by tokens last week

| Rank | Model | Lab | Tokens |
| --- | --- | --- | --- |
| 39 | [mimo-v2.5-pro](https://opencode.ai/data/xiaomi/mimo-v2-5-pro.md) | Xiaomi | 11B |
| 40 | [omen-alpha](https://opencode.ai/data/unknown/omen-alpha.md) | - | 10B |
| 41 | [gemini-4-argon](https://opencode.ai/data/google/gemini-4-argon.md) | Google | 7.1B |
| 42 | [jev-1.13](https://opencode.ai/data/unknown/jev-1-13.md) | - | 5.6B |
| 43 | [iceman-contributor](https://opencode.ai/data/unknown/iceman-contributor.md) | - | 5.1B |
| 44 | [kimi-k2.6](https://opencode.ai/data/moonshotai/kimi-k2-6.md) | Moonshot | 2.6B |
| 45 | [glm-5.1](https://opencode.ai/data/zhipuai/glm-5-1.md) | Zhipu | 1.1B |
| 46 | [qwen3.6-plus](https://opencode.ai/data/alibaba/qwen3-6-plus.md) | Qwen | 941M |
| 47 | [minimax-m2.7](https://opencode.ai/data/minimax/minimax-m2-7.md) | MiniMax | 796M |
| 48 | [grok-4.6](https://opencode.ai/data/xai/grok-4-6.md) | xAI | 663M |

## 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.