# LongCat-2.0 Usage, Cost & Rank | OpenCode Data

> LongCat-2.0 ranked #28 by tokens across OpenCode last week, with 0.1% of tokens over the past two months. LongCat-2.0 costs $0.30 per 1M input tokens and $1.20 per 1M output tokens.

Meituan LongCat-2.0, a reasoning model with tool calling and a 1M-token context window

- Page: https://opencode.ai/data/meituan/longcat-2-0
- JSON: https://opencode.ai/data/meituan/longcat-2-0.json
- Model ID: meituan/longcat-2.0
- Lab: Meituan
- Updated: 2026-10-02T08:39:37.000Z

## Model facts

| Fact | Value |
| --- | --- |
| Context window | 1M |
| Max output | 131K |
| Knowledge cutoff | - |
| Release date | 2026-06-30 |
| Input modalities | text |
| 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 | #28 |
| Tokens | 553B |
| Share of all tokens | 0.1% |
| Change vs previous 2 months | +100% |
| Unique users | 46K |
| Completed sessions | 249,321 |
| Average tokens per session | 2.2M |
| Average cost per session | $0.0388 |
| Total spend | $9,668 |
| Input tokens served from cache | 96.2% |
| Weekly retention | 65.5% |

## Daily usage: past 2 months

| Date | Tokens | Unique users | Sessions |
| --- | --- | --- | --- |
| 2026-08-11 | 108B | 2K | 0 |
| 2026-08-12 | 27B | 924 | 0 |
| 2026-08-13 | 0 | 0 | 0 |
| 2026-08-14 | 0 | 0 | 0 |
| 2026-08-15 | 0 | 0 | 0 |
| 2026-08-16 | 0 | 0 | 0 |
| 2026-08-17 | 0 | 0 | 0 |
| 2026-08-18 | 0 | 0 | 0 |
| 2026-08-19 | 0 | 0 | 0 |
| 2026-08-20 | 0 | 0 | 0 |
| 2026-08-21 | 0 | 0 | 0 |
| 2026-08-22 | 0 | 0 | 0 |
| 2026-08-23 | 0 | 0 | 0 |
| 2026-08-24 | 4.3B | 825 | 824 |
| 2026-08-25 | 16B | 1.6K | 1,835 |
| 2026-08-26 | 19B | 1.6K | 2,070 |
| 2026-08-27 | 23B | 1.7K | 2,582 |
| 2026-08-28 | 23B | 1.4K | 2,093 |
| 2026-08-29 | 17B | 1.1K | 2,217 |
| 2026-08-30 | 15B | 1K | 1,553 |
| 2026-08-31 | 23B | 1.6K | 3,666 |
| 2026-09-01 | 20B | 1.5K | 3,610 |
| 2026-09-02 | 22B | 1.5K | 2,582 |
| 2026-09-03 | 24B | 1.6K | 3,039 |
| 2026-09-04 | 20B | 1.4K | 3,947 |
| 2026-09-05 | 11B | 982 | 2,041 |
| 2026-09-06 | 11B | 889 | 2,016 |
| 2026-09-07 | 15B | 1.3K | 4,085 |
| 2026-09-08 | 16B | 1.2K | 7,615 |
| 2026-09-09 | 13B | 1K | 6,384 |
| 2026-09-10 | 11B | 1.3K | 6,197 |
| 2026-09-11 | 8.2B | 1.1K | 4,451 |
| 2026-09-12 | 5.9B | 828 | 4,232 |
| 2026-09-13 | 6.2B | 797 | 2,972 |
| 2026-09-14 | 8B | 1.1K | 4,140 |
| 2026-09-15 | 7.7B | 1.1K | 3,284 |
| 2026-09-16 | 5.5B | 1.1K | 3,637 |
| 2026-09-17 | 6.7B | 1.2K | 3,762 |
| 2026-09-18 | 5.3B | 1K | 3,225 |
| 2026-09-19 | 3.9B | 855 | 4,356 |
| 2026-09-20 | 5.3B | 906 | 6,407 |
| 2026-09-21 | 5.9B | 1.1K | 10,736 |
| 2026-09-22 | 6.5B | 1.1K | 12,596 |
| 2026-09-23 | 4.8B | 917 | 13,082 |
| 2026-09-24 | 4B | 899 | 11,566 |
| 2026-09-25 | 5.3B | 795 | 12,793 |
| 2026-09-26 | 3.6B | 786 | 17,277 |
| 2026-09-27 | 4.6B | 788 | 12,333 |
| 2026-09-28 | 5.1B | 953 | 15,159 |
| 2026-09-29 | 4.8B | 914 | 14,260 |
| 2026-09-30 | 3.1B | 777 | 13,548 |
| 2026-10-01 | 3.9B | 722 | 12,892 |
| 2026-10-02 | 1.1B | 308 | 4,257 |

## Top countries: past 2 months

| Rank | Country | Tokens | Share |
| --- | --- | --- | --- |
| 1 | China | 78B | 14% |
| 2 | United States | 63B | 11.3% |
| 3 | India | 31B | 5.6% |
| 4 | Russia | 27B | 4.9% |
| 5 | Brazil | 25B | 4.5% |
| 6 | Germany | 24B | 4.2% |
| 7 | Indonesia | 14B | 2.5% |
| 8 | Japan | 14B | 2.5% |
| 9 | United Kingdom | 13B | 2.4% |
| 10 | Poland | 12B | 2.2% |
| 11 | Singapore | 11B | 2% |
| 12 | Argentina | 11B | 2% |
| 13 | Hong Kong | 11B | 2% |
| 14 | Mexico | 10B | 1.8% |
| 15 | Spain | 9.9B | 1.8% |

## Nearby models by tokens last week

| Rank | Model | Lab | Tokens |
| --- | --- | --- | --- |
| 24 | [qwen3.7-plus](https://opencode.ai/data/alibaba/qwen3-7-plus.md) | Qwen | 76B |
| 25 | [glm-5.2](https://opencode.ai/data/zhipuai/glm-5-2.md) | Zhipu | 61B |
| 26 | [kimi-k3](https://opencode.ai/data/moonshotai/kimi-k3.md) | Moonshot | 45B |
| 27 | [mimo-v2.5-pro](https://opencode.ai/data/xiaomi/mimo-v2-5-pro.md) | Xiaomi | 42B |
| 28 | [longcat-2.0](https://opencode.ai/data/meituan/longcat-2-0.md) | Meituan | 26B |
| 29 | [qwen3.8-max](https://opencode.ai/data/alibaba/qwen3-8-max.md) | Qwen | 26B |
| 30 | [hy3](https://opencode.ai/data/tencent/hy3.md) | Tencent | 17B |
| 31 | [minimax-m2.7](https://opencode.ai/data/minimax/minimax-m2-7.md) | MiniMax | 15B |
| 32 | [hy4-preview](https://opencode.ai/data/tencent/hy4-preview.md) | Tencent | 13B |
| 33 | [omen-alpha](https://opencode.ai/data/unknown/omen-alpha.md) | - | 12B |

## Benchmarks

| Benchmark | Score | Metric | Source |
| --- | --- | --- | --- |
| SWE-Bench Pro | 59.5 | resolve rate | https://github.com/meituan-longcat/longcat-2.0 |
| SWE-Bench Multilingual | 77.3 | resolve rate | https://github.com/meituan-longcat/longcat-2.0 |
| Terminal-Bench | 70.8 | success rate | https://github.com/meituan-longcat/longcat-2.0 |
| GPQA Diamond | 88.9 | accuracy | https://github.com/meituan-longcat/longcat-2.0 |
| BrowseComp | 79.9 | accuracy | https://github.com/meituan-longcat/longcat-2.0 |
| IFEval | 90 | accuracy | https://github.com/meituan-longcat/longcat-2.0 |
| FORTE | 73.2 | success rate | https://github.com/meituan-longcat/longcat-2.0 |

## 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.