# cat-jam Usage, Cost & Rank | OpenCode Data

> cat-jam ranked #21 by tokens across OpenCode last week, with 0.0% of tokens over the past two months.

- Page: https://opencode.ai/data/unknown/cat-jam
- JSON: https://opencode.ai/data/unknown/cat-jam.json
- Model ID: cat-jam
- Lab: Unknown
- Updated: 2026-10-14T06:55:43.000Z

## OpenCode usage: past 2 months

| Metric | Value |
| --- | --- |
| Rank by tokens last week | #21 |
| Tokens | 222B |
| Share of all tokens | 0.0% |
| Change vs previous 2 months | +100% |
| Unique users | 10K |
| Completed sessions | 211,565 |
| Average tokens per session | 1.1M |
| Average cost per session | $0.0000 |
| Total spend | $0 |
| Input tokens served from cache | 96.2% |
| Weekly retention | - |

## Daily usage: past 2 months

| Date | Tokens | Unique users | Sessions |
| --- | --- | --- | --- |
| 2026-10-13 | 135B | 6.7K | 129,644 |
| 2026-10-14 | 88B | 3.8K | 81,921 |

## Top countries: past 2 months

| Rank | Country | Tokens | Share |
| --- | --- | --- | --- |
| 1 | United States | 33B | 14.7% |
| 2 | Netherlands | 22B | 9.9% |
| 3 | United Kingdom | 19B | 8.6% |
| 4 | India | 17B | 7.6% |
| 5 | Brazil | 11B | 5.1% |
| 6 | Germany | 11B | 4.8% |
| 7 | Indonesia | 8.1B | 3.6% |
| 8 | Türkiye | 5.4B | 2.4% |
| 9 | Japan | 5.1B | 2.3% |
| 10 | France | 5B | 2.3% |
| 11 | Spain | 4.8B | 2.2% |
| 12 | Canada | 4.1B | 1.8% |
| 13 | Philippines | 4.1B | 1.8% |
| 14 | Colombia | 3.9B | 1.8% |
| 15 | Australia | 3.4B | 1.5% |

## Nearby models by tokens last week

| Rank | Model | Lab | Tokens |
| --- | --- | --- | --- |
| 17 | [mimo-v2.5](https://opencode.ai/data/xiaomi/mimo-v2-5.md) | Xiaomi | 315B |
| 18 | [claude-haiku-5-5](https://opencode.ai/data/anthropic/claude-haiku-5-5.md) | Anthropic | 258B |
| 19 | [fledge-alpha](https://opencode.ai/data/unknown/fledge-alpha.md) | - | 256B |
| 20 | [qwen3.8-flash](https://opencode.ai/data/alibaba/qwen3-8-flash.md) | Qwen | 234B |
| 21 | [cat-jam](https://opencode.ai/data/unknown/cat-jam.md) | - | 222B |
| 22 | [minimax-m3](https://opencode.ai/data/minimax/minimax-m3.md) | MiniMax | 172B |
| 23 | [ling-3.1-flash](https://opencode.ai/data/inclusionai/ling-3-1-flash.md) | inclusionAI | 129B |
| 24 | [kimi-k2.7-code](https://opencode.ai/data/moonshotai/kimi-k2-7-code.md) | Moonshot | 115B |
| 25 | [gpt-5.6-luna](https://opencode.ai/data/openai/gpt-5-6-luna.md) | OpenAI | 112B |
| 26 | [glm-5.3](https://opencode.ai/data/zhipuai/glm-5-3.md) | Zhipu | 98B |

## 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.