# Qwen3.6 Plus Usage, Cost & Rank | OpenCode Data

> Qwen3.6 Plus ranked #39 by tokens across OpenCode last week, with 0.0% of tokens over the past two months. Qwen3.6 Plus costs $0.50 per 1M input tokens and $3.00 per 1M output tokens.

Earlier Qwen multimodal workhorse for million-token agent and document tasks

- Page: https://opencode.ai/data/alibaba/qwen3-6-plus
- JSON: https://opencode.ai/data/alibaba/qwen3-6-plus.json
- Model ID: alibaba/qwen3.6-plus
- Lab: Alibaba
- Updated: 2026-10-02T08:39:37.000Z

## Model facts

| Fact | Value |
| --- | --- |
| Context window | 1M |
| Max output | 66K |
| Knowledge cutoff | 2025-04 |
| Release date | 2026-04-02 |
| Input modalities | text, image, video |
| Output modalities | text |
| Reasoning | Yes |
| Tool calling | Yes |
| Open weights | No |

## Pricing: USD per 1M tokens

| Input | Output | Cached input | Cache write |
| --- | --- | --- | --- |
| $0.50 | $3.00 | $0.05 | $0.63 |

## OpenCode usage: past 2 months

| Metric | Value |
| --- | --- |
| Rank by tokens last week | #39 |
| Tokens | 126B |
| Share of all tokens | 0.0% |
| Change vs previous 2 months | -62% |
| Unique users | 68K |
| Completed sessions | 110,589 |
| Average tokens per session | 1.1M |
| Average cost per session | $0.6050 |
| Total spend | $66,909 |
| Input tokens served from cache | 38.2% |
| Weekly retention | 54.3% |

## Daily usage: past 2 months

| Date | Tokens | Unique users | Sessions |
| --- | --- | --- | --- |
| 2026-08-08 | 2.7B | 1.6K | 1,442 |
| 2026-08-09 | 3.3B | 1.6K | 1,817 |
| 2026-08-10 | 4.8B | 2.1K | 3,169 |
| 2026-08-11 | 4.8B | 2.9K | 1,215 |
| 2026-08-12 | 7.9B | 2.1K | 21 |
| 2026-08-13 | 7.2B | 2.2K | 25 |
| 2026-08-14 | 5.6B | 2.2K | 27 |
| 2026-08-15 | 4B | 2.1K | 35 |
| 2026-08-16 | 1.9B | 2.4K | 22 |
| 2026-08-17 | 1.3B | 3.3K | 9 |
| 2026-08-18 | 3.5B | 2.4K | 4,445 |
| 2026-08-19 | 4.2B | 2.6K | 1,947 |
| 2026-08-20 | 3.6B | 2.3K | 1,836 |
| 2026-08-21 | 3.1B | 2.4K | 1,683 |
| 2026-08-22 | 2.2B | 1.3K | 868 |
| 2026-08-23 | 1.9B | 1.2K | 1,008 |
| 2026-08-24 | 3.8B | 1.6K | 1,922 |
| 2026-08-25 | 3.2B | 1.5K | 1,512 |
| 2026-08-26 | 3B | 1.4K | 1,893 |
| 2026-08-27 | 2.5B | 1.2K | 1,087 |
| 2026-08-28 | 2.3B | 1.1K | 1,178 |
| 2026-08-29 | 1.3B | 889 | 627 |
| 2026-08-30 | 1.1B | 768 | 666 |
| 2026-08-31 | 2.3B | 1.2K | 1,149 |
| 2026-09-01 | 2.3B | 1.1K | 1,143 |
| 2026-09-02 | 2.3B | 1K | 1,128 |
| 2026-09-03 | 2.1B | 1.1K | 1,220 |
| 2026-09-04 | 1.6B | 962 | 1,253 |
| 2026-09-05 | 1.3B | 696 | 898 |
| 2026-09-06 | 1.1B | 693 | 980 |
| 2026-09-07 | 2B | 899 | 2,433 |
| 2026-09-08 | 2B | 783 | 2,573 |
| 2026-09-09 | 2.3B | 765 | 2,521 |
| 2026-09-10 | 1.9B | 1K | 3,237 |
| 2026-09-11 | 1.6B | 903 | 3,075 |
| 2026-09-12 | 1.1B | 687 | 1,942 |
| 2026-09-13 | 1.1B | 712 | 2,089 |
| 2026-09-14 | 2.1B | 1K | 4,701 |
| 2026-09-15 | 1.9B | 1K | 4,297 |
| 2026-09-16 | 1.7B | 1K | 3,244 |
| 2026-09-17 | 1.7B | 1.1K | 9,932 |
| 2026-09-18 | 1.8B | 924 | 4,970 |
| 2026-09-19 | 1.5B | 740 | 3,072 |
| 2026-09-20 | 1.1B | 769 | 3,315 |
| 2026-09-21 | 2.5B | 1K | 4,298 |
| 2026-09-22 | 1.8B | 1K | 5,517 |
| 2026-09-23 | 1.8B | 804 | 3,480 |
| 2026-09-24 | 1.4B | 782 | 2,638 |
| 2026-09-25 | 1.1B | 638 | 2,377 |
| 2026-09-26 | 784M | 627 | 1,828 |
| 2026-09-27 | 885M | 642 | 1,899 |
| 2026-09-28 | 219M | 271 | 593 |
| 2026-09-29 | 0 | 0 | 0 |
| 2026-09-30 | 0 | 0 | 0 |
| 2026-10-01 | 507K | 24 | 29 |
| 2026-10-02 | 23M | 159 | 304 |

## Top countries: past 2 months

| Rank | Country | Tokens | Share |
| --- | --- | --- | --- |
| 1 | United States | 15B | 11.8% |
| 2 | Brazil | 7.6B | 6% |
| 3 | China | 7.6B | 6% |
| 4 | Spain | 6.7B | 5.3% |
| 5 | Germany | 6.4B | 5.1% |
| 6 | Colombia | 5.1B | 4% |
| 7 | India | 4.6B | 3.7% |
| 8 | Indonesia | 4.6B | 3.6% |
| 9 | Argentina | 4.6B | 3.6% |
| 10 | Mexico | 4.4B | 3.5% |
| 11 | Russia | 4.2B | 3.3% |
| 12 | United Kingdom | 4B | 3.2% |
| 13 | France | 3.3B | 2.6% |
| 14 | Chile | 2.9B | 2.3% |
| 15 | Netherlands | 2.4B | 1.9% |

## Nearby models by tokens last week

| Rank | Model | Lab | Tokens |
| --- | --- | --- | --- |
| 35 | [jev-1.13](https://opencode.ai/data/unknown/jev-1-13.md) | - | 6B |
| 36 | [kimi-k2.6](https://opencode.ai/data/moonshotai/kimi-k2-6.md) | Moonshot | 5.5B |
| 37 | [grok-4.6](https://opencode.ai/data/xai/grok-4-6.md) | xAI | 2.8B |
| 38 | [glm-5.1](https://opencode.ai/data/zhipuai/glm-5-1.md) | Zhipu | 2.5B |
| 39 | [qwen3.6-plus](https://opencode.ai/data/alibaba/qwen3-6-plus.md) | Qwen | 1.9B |
| 40 | [test-novita-dsf4.1](https://opencode.ai/data/deepseek/test-novita-dsf4-1.md) | DeepSeek | 986M |
| 41 | [qwen3.7-max](https://opencode.ai/data/alibaba/qwen3-7-max.md) | Qwen | 920M |
| 42 | [minimax-m2.5](https://opencode.ai/data/minimax/minimax-m2-5.md) | MiniMax | 720M |
| 43 | [gpt-5-nano](https://opencode.ai/data/openai/gpt-5-nano.md) | OpenAI | 289M |
| 44 | [test](https://opencode.ai/data/openai/test.md) | OpenAI | 218M |

## 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.