Model Comparison

Gemini Diffusion vs MiMo-V2-Flash

MiMo-V2-Flash significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

Gemini Diffusion outperforms in 0 benchmarks, while MiMo-V2-Flash is better at 3 benchmarks (AIME 2025, GPQA, SWE-Bench Verified).

MiMo-V2-Flash significantly outperforms across most benchmarks.

Tue Apr 21 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Tue Apr 21 2026 • llm-stats.com
Google
Gemini Diffusion
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Xiaomi
MiMo-V2-Flash
Input tokens$0.10
Output tokens$0.30
Best providerXiaomi
Notice missing or incorrect data?Start an Issue→

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).

Google
Gemini Diffusion
Input- tokens
Output- tokens
Xiaomi
MiMo-V2-Flash
Input256,000 tokens
Output16,384 tokens
Tue Apr 21 2026 • llm-stats.com

License

Usage and distribution terms

Gemini Diffusion is licensed under a proprietary license, while MiMo-V2-Flash uses MIT.

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

Gemini Diffusion

Proprietary

Closed source

MiMo-V2-Flash

MIT

Open weights

Release Timeline

When each model was launched

Gemini Diffusion was released on 2025-05-20, while MiMo-V2-Flash was released on 2025-12-16.

MiMo-V2-Flash is 7 months newer than Gemini Diffusion.

Gemini Diffusion

May 20, 2025

11 months ago

MiMo-V2-Flash

Dec 16, 2025

4 months ago

7mo newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

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Key Takeaways

Google
Xiaomi
Larger context window (256,000 tokens)
Has open weights
Higher AIME 2025 score (94.1% vs 23.3%)
Higher GPQA score (83.7% vs 40.4%)
Higher SWE-Bench Verified score (73.4% vs 22.9%)

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemini Diffusion
Xiaomi
MiMo-V2-Flash

FAQ

Common questions about Gemini Diffusion vs MiMo-V2-Flash

MiMo-V2-Flash significantly outperforms across most benchmarks. Gemini Diffusion is made by Google and MiMo-V2-Flash is made by Xiaomi. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
Gemini Diffusion scores HumanEval: 89.6%, MBPP: 76.0%, Global-MMLU-Lite: 69.1%, LBPP (v2): 56.8%, BigCodeBench: 45.4%. MiMo-V2-Flash scores AIME 2025: 94.1%, Arena-Hard v2: 86.2%, MMLU-Pro: 84.9%, HMMT 2025: 84.4%, GPQA: 83.7%.
Gemini Diffusion supports an unknown number of tokens and MiMo-V2-Flash supports 256K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include licensing (Proprietary vs MIT). See the full comparison above for benchmark-by-benchmark results.
Gemini Diffusion is developed by Google and MiMo-V2-Flash is developed by Xiaomi.