# MiMo-V2.6-Pro Usage, Cost & Rank | OpenCode Data

> MiMo-V2.6-Pro ranked #14 by tokens across OpenCode last week, with 0.1% of tokens over the past two months. MiMo-V2.6-Pro costs $0.47 per 1M input tokens and $0.94 per 1M output tokens.

Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution

- Page: https://opencode.ai/data/xiaomi/mimo-v2-6-pro
- JSON: https://opencode.ai/data/xiaomi/mimo-v2-6-pro.json
- Model ID: xiaomi/mimo-v2.6-pro
- Lab: Xiaomi
- Updated: 2026-10-02T08:39:37.000Z

## Model facts

| Fact | Value |
| --- | --- |
| Context window | 1M |
| Max output | 131K |
| Knowledge cutoff | - |
| Release date | 2026-09-22 |
| Input modalities | text, image, audio, video |
| Output modalities | text |
| Reasoning | Yes |
| Tool calling | Yes |
| Open weights | Yes |
| Weights | [Hugging Face](https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Pro-RL) |

## Pricing: USD per 1M tokens

| Input | Output | Cached input | Cache write |
| --- | --- | --- | --- |
| $0.47 | $0.94 | $0.0050 | $0.47 |

## OpenCode usage: past 2 months

| Metric | Value |
| --- | --- |
| Rank by tokens last week | #14 |
| Tokens | 857B |
| Share of all tokens | 0.1% |
| Change vs previous 2 months | +100% |
| Unique users | 47K |
| Completed sessions | 211,677 |
| Average tokens per session | 4M |
| Average cost per session | $0.1055 |
| Total spend | $22,327 |
| Input tokens served from cache | 96.3% |
| Weekly retention | - |

## Daily usage: past 2 months

| Date | Tokens | Unique users | Sessions |
| --- | --- | --- | --- |
| 2026-09-21 | 6.9B | 980 | 2,887 |
| 2026-09-22 | 120B | 7.9K | 34,363 |
| 2026-09-23 | 100B | 5.9K | 29,002 |
| 2026-09-24 | 89B | 4.8K | 24,145 |
| 2026-09-25 | 76B | 3.8K | 18,373 |
| 2026-09-26 | 66B | 3.1K | 13,598 |
| 2026-09-27 | 58B | 3K | 14,175 |
| 2026-09-28 | 87B | 4.3K | 18,342 |
| 2026-09-29 | 86B | 4.2K | 18,901 |
| 2026-09-30 | 78B | 3.9K | 18,627 |
| 2026-10-01 | 70B | 3.5K | 14,775 |
| 2026-10-02 | 19B | 1.5K | 4,489 |

## Top countries: past 2 months

| Rank | Country | Tokens | Share |
| --- | --- | --- | --- |
| 1 | United States | 118B | 13.8% |
| 2 | China | 68B | 7.9% |
| 3 | Germany | 46B | 5.4% |
| 4 | Brazil | 45B | 5.3% |
| 5 | Spain | 36B | 4.2% |
| 6 | Japan | 33B | 3.9% |
| 7 | France | 29B | 3.4% |
| 8 | India | 29B | 3.4% |
| 9 | Canada | 23B | 2.7% |
| 10 | United Kingdom | 22B | 2.6% |
| 11 | Singapore | 19B | 2.3% |
| 12 | Poland | 18B | 2.1% |
| 13 | Italy | 16B | 1.9% |
| 14 | Australia | 16B | 1.9% |
| 15 | Indonesia | 16B | 1.8% |

## Nearby models by tokens last week

| Rank | Model | Lab | Tokens |
| --- | --- | --- | --- |
| 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 |
| 13 | [deepseek-v4-pro](https://opencode.ai/data/deepseek/deepseek-v4-pro.md) | DeepSeek | 465B |
| 14 | [mimo-v2.6-pro](https://opencode.ai/data/xiaomi/mimo-v2-6-pro.md) | Xiaomi | 464B |
| 15 | [nemotron-3.5-lightning](https://opencode.ai/data/nvidia/nemotron-3-5-lightning.md) | NVIDIA | 267B |
| 16 | [ling-3.0-flash-fin](https://opencode.ai/data/inclusionai/ling-3-0-flash-fin.md) | inclusionAI | 256B |
| 17 | [qwen3.8-flash](https://opencode.ai/data/alibaba/qwen3-8-flash.md) | Qwen | 256B |
| 18 | [gpt-5.6-luna](https://opencode.ai/data/openai/gpt-5-6-luna.md) | OpenAI | 195B |
| 19 | [minimax-m3](https://opencode.ai/data/minimax/minimax-m3.md) | MiniMax | 181B |

## Benchmarks

| Benchmark | Score | Metric | Source |
| --- | --- | --- | --- |
| DeepSWE | 71.9 | score | https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL |
| ProgramBench | 26.5 | score | https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL |
| MiMo Code Bench | 63.2 | score | https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL |
| AutomationBench | 53.1 | score | https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL |
| Toolathlon-Verified | 76.9 | score | https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL |
| GDPval-AA | 1673 | Elo | https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL |
| Agents' Last Exam | 31.6 | score | https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL |
| Terminal-Bench | 34.9 | score | https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL |
| Terminal-Bench | 89.9 | score | https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL |
| OSWorld-Verified | 82 | score | https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL |
| JobBench | 62 | score | https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL |
| CyberGym | 94 | score | https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL |
| MiMo Cyber Bench | 80.2 | score | https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL |
| ExploitGym | 17.8 | score | https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL |
| ExploitBench | 47.9 | score | https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL |
| SEC-Bench Pro | 66.3 | score | https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL |
| MiMo VisualCoding | 72.3 | score | https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL |

## 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.