Model Comparison

MiMo-V2-Flash vs Qwen2-VL-72B-Instruct

Comparing MiMo-V2-Flash and Qwen2-VL-72B-Instruct across benchmarks, pricing, and capabilities.

Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

MiMo-V2-Flash and Qwen2-VL-72B-Instruct don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Wed Apr 15 2026 • llm-stats.com
Xiaomi
MiMo-V2-Flash
Input tokens$0.10
Output tokens$0.30
Best providerXiaomi
Alibaba Cloud / Qwen Team
Qwen2-VL-72B-Instruct
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

235.6B diff

MiMo-V2-Flash has 235.6B more parameters than Qwen2-VL-72B-Instruct, making it 321.0% larger.

Xiaomi
MiMo-V2-Flash
309.0Bparameters
Alibaba Cloud / Qwen Team
Qwen2-VL-72B-Instruct
73.4Bparameters
309.0B
MiMo-V2-Flash
73.4B
Qwen2-VL-72B-Instruct

Context Window

Maximum input and output token capacity

Only MiMo-V2-Flash specifies input context (256,000 tokens). Only MiMo-V2-Flash specifies output context (16,384 tokens).

Xiaomi
MiMo-V2-Flash
Input256,000 tokens
Output16,384 tokens
Alibaba Cloud / Qwen Team
Qwen2-VL-72B-Instruct
Input- tokens
Output- tokens
Wed Apr 15 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen2-VL-72B-Instruct supports multimodal inputs, whereas MiMo-V2-Flash does not.

Qwen2-VL-72B-Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.

MiMo-V2-Flash

Text
Images
Audio
Video

Qwen2-VL-72B-Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

MiMo-V2-Flash is licensed under MIT, while Qwen2-VL-72B-Instruct uses tongyi-qianwen.

License differences may affect how you can use these models in commercial or open-source projects.

MiMo-V2-Flash

MIT

Open weights

Qwen2-VL-72B-Instruct

tongyi-qianwen

Open weights

Release Timeline

When each model was launched

MiMo-V2-Flash was released on 2025-12-16, while Qwen2-VL-72B-Instruct was released on 2024-08-29.

MiMo-V2-Flash is 16 months newer than Qwen2-VL-72B-Instruct.

MiMo-V2-Flash

Dec 16, 2025

4 months ago

1.3yr newer
Qwen2-VL-72B-Instruct

Aug 29, 2024

1.6 years ago

Knowledge Cutoff

When training data ends

Qwen2-VL-72B-Instruct has a documented knowledge cutoff of 2023-06-30, while MiMo-V2-Flash's cutoff date is not specified.

We can confirm Qwen2-VL-72B-Instruct's training data extends to 2023-06-30, but cannot make a direct comparison without MiMo-V2-Flash's cutoff date.

MiMo-V2-Flash

—

Qwen2-VL-72B-Instruct

Jun 2023

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Xiaomi
Larger context window (256,000 tokens)
Alibaba Cloud / Qwen Team

Qwen2-VL-72B-Instruct

View details

Alibaba Cloud / Qwen Team

Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
Xiaomi
MiMo-V2-Flash
Alibaba Cloud / Qwen Team
Qwen2-VL-72B-Instruct

FAQ

Common questions about MiMo-V2-Flash vs Qwen2-VL-72B-Instruct

MiMo-V2-Flash (Xiaomi) and Qwen2-VL-72B-Instruct (Alibaba Cloud / Qwen Team) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
MiMo-V2-Flash scores AIME 2025: 94.1%, Arena-Hard v2: 86.2%, MMLU-Pro: 84.9%, HMMT 2025: 84.4%, GPQA: 83.7%. Qwen2-VL-72B-Instruct scores DocVQAtest: 96.5%, VCR_en_easy: 91.9%, ChartQA: 88.3%, OCRBench: 87.7%, MMBench_test: 86.5%.
MiMo-V2-Flash supports 256K tokens and Qwen2-VL-72B-Instruct supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include multimodal support (no vs yes), licensing (MIT vs tongyi-qianwen). See the full comparison above for benchmark-by-benchmark results.
MiMo-V2-Flash is developed by Xiaomi and Qwen2-VL-72B-Instruct is developed by Alibaba Cloud / Qwen Team.