# LongCat-2.5-Preview Usage, Cost & Rank | OpenCode Data

> LongCat-2.5-Preview ranked #7 by tokens across OpenCode last week, with 0.3% of tokens over the past two months. LongCat-2.5-Preview costs $0.30 per 1M input tokens and $1.20 per 1M output tokens.

Meituan's multimodal reasoning model for coding and agent tasks, with image understanding and a 1M-token context window

- Page: https://opencode.ai/data/meituan/longcat-2-5-preview
- JSON: https://opencode.ai/data/meituan/longcat-2-5-preview.json
- Model ID: meituan/longcat-2.5-preview
- Lab: Meituan
- Updated: 2026-10-02T08:39:37.000Z

## Model facts

| Fact | Value |
| --- | --- |
| Context window | 1M |
| Max output | 131K |
| Knowledge cutoff | - |
| Release date | 2026-09-25 |
| Input modalities | text, image |
| Output modalities | text |
| Reasoning | Yes |
| Tool calling | Yes |
| Open weights | No |

## Pricing: USD per 1M tokens

| Input | Output | Cached input | Cache write |
| --- | --- | --- | --- |
| $0.30 | $1.20 | $0.0060 | - |

## OpenCode usage: past 2 months

| Metric | Value |
| --- | --- |
| Rank by tokens last week | #7 |
| Tokens | 2.6T |
| Share of all tokens | 0.3% |
| Change vs previous 2 months | +100% |
| Unique users | 46K |
| Completed sessions | 2,293,613 |
| Average tokens per session | 1.2M |
| Average cost per session | $0.0000 |
| Total spend | $0 |
| Input tokens served from cache | 96% |
| Weekly retention | - |

## Daily usage: past 2 months

| Date | Tokens | Unique users | Sessions |
| --- | --- | --- | --- |
| 2026-09-25 | 4.9K | 2 | 1 |
| 2026-09-26 | 136B | 3.4K | 101,499 |
| 2026-09-27 | 359B | 6.7K | 217,834 |
| 2026-09-28 | 529B | 8.4K | 344,505 |
| 2026-09-29 | 543B | 8.4K | 413,046 |
| 2026-09-30 | 545B | 8.1K | 499,419 |
| 2026-10-01 | 427B | 7.5K | 529,169 |
| 2026-10-02 | 105B | 3.1K | 188,140 |

## Top countries: past 2 months

| Rank | Country | Tokens | Share |
| --- | --- | --- | --- |
| 1 | United States | 289B | 10.9% |
| 2 | India | 224B | 8.5% |
| 3 | China | 223B | 8.4% |
| 4 | Brazil | 143B | 5.4% |
| 5 | Germany | 130B | 4.9% |
| 6 | Russia | 95B | 3.6% |
| 7 | Indonesia | 72B | 2.7% |
| 8 | Spain | 66B | 2.5% |
| 9 | France | 59B | 2.2% |
| 10 | Argentina | 54B | 2% |
| 11 | Japan | 53B | 2% |
| 12 | United Kingdom | 53B | 2% |
| 13 | Türkiye | 51B | 1.9% |
| 14 | Egypt | 48B | 1.8% |
| 15 | Vietnam | 47B | 1.8% |

## Nearby models by tokens last week

| Rank | Model | Lab | Tokens |
| --- | --- | --- | --- |
| 3 | [muse-spark-1.3-contributor](https://opencode.ai/data/meta/muse-spark-1-3-contributor.md) | Meta | 31T |
| 4 | [mimo-v2.6-flash](https://opencode.ai/data/xiaomi/mimo-v2-6-flash.md) | Xiaomi | 8.8T |
| 5 | [deepseek-v4-flash](https://opencode.ai/data/deepseek/deepseek-v4-flash.md) | DeepSeek | 5.7T |
| 6 | [nemotron-3-ultra](https://opencode.ai/data/nvidia/nemotron-3-ultra.md) | NVIDIA | 3.6T |
| 7 | [longcat-2.5-preview](https://opencode.ai/data/meituan/longcat-2-5-preview.md) | Meituan | 2.6T |
| 8 | [glm-5.3-flash](https://opencode.ai/data/zhipuai/glm-5-3-flash.md) | Zhipu | 2.1T |
| 9 | [mimo-v2.5](https://opencode.ai/data/xiaomi/mimo-v2-5.md) | Xiaomi | 794B |
| 10 | [muse-spark-1.2-contributor](https://opencode.ai/data/meta/muse-spark-1-2-contributor.md) | Meta | 738B |
| 11 | [deepseek-v4-flash-vision-exp](https://opencode.ai/data/deepseek/deepseek-v4-flash-vision-exp.md) | DeepSeek | 687B |
| 12 | [gpt-6-luna](https://opencode.ai/data/openai/gpt-6-luna.md) | OpenAI | 640B |

## 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.