Model Comparison

DeepSeek R1 Distill Qwen 14B vs MiMo-V2-FlashWhich is better in 2026?

MiMo-V2-Flash significantly outperforms across most benchmarks.

Verdict: DeepSeek R1 Distill Qwen 14B vs MiMo-V2-Flash — which is better?

DeepSeek R1 Distill Qwen 14B (by DeepSeek) and MiMo-V2-Flash (by Xiaomi) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

DeepSeek R1 Distill Qwen 14B outperforms in 0 benchmarks, while MiMo-V2-Flash is better at 1 benchmark (GPQA). MiMo-V2-Flash significantly outperforms across most benchmarks.

Choose DeepSeek R1 Distill Qwen 14B if…

  • you are already invested in the DeepSeek ecosystem

Choose MiMo-V2-Flash if…

  • you want the strongest raw capability — it leads on 1 of 1 shared benchmarks
  • you want the most recent training data — it shipped Dec 2025

Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

DeepSeek R1 Distill Qwen 14B outperforms in 0 benchmarks, while MiMo-V2-Flash is better at 1 benchmark (GPQA).

MiMo-V2-Flash significantly outperforms across most benchmarks.

Tue Jun 23 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

294.2B diff

MiMo-V2-Flash has 294.2B more parameters than DeepSeek R1 Distill Qwen 14B, making it 1987.8% larger.

DeepSeek
DeepSeek R1 Distill Qwen 14B
14.8Bparameters
Xiaomi
MiMo-V2-Flash
309.0Bparameters
14.8B
DeepSeek R1 Distill Qwen 14B
309.0B
MiMo-V2-Flash

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).

DeepSeek
DeepSeek R1 Distill Qwen 14B
Input- tokens
Output- tokens
Xiaomi
MiMo-V2-Flash
Input256,000 tokens
Output16,384 tokens
Tue Jun 23 2026 • llm-stats.com

License

Usage and distribution terms

Both models are licensed under MIT.

Both models share the same licensing terms, providing consistent usage rights.

DeepSeek R1 Distill Qwen 14B

MIT

Open weights

MiMo-V2-Flash

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Distill Qwen 14B was released on 2025-01-20, while MiMo-V2-Flash was released on 2025-12-16.

MiMo-V2-Flash is 11 months newer than DeepSeek R1 Distill Qwen 14B.

DeepSeek R1 Distill Qwen 14B

Jan 20, 2025

1.4 years ago

MiMo-V2-Flash

Dec 16, 2025

6 months ago

11mo 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

Notice missing or incorrect data?Start an Issue discussion

Key Takeaways

No standout differentiators in the data we have for this pair.

Larger context window (256,000 tokens)
Higher GPQA score (83.7% vs 59.1%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek R1 Distill Qwen 14B
Xiaomi
MiMo-V2-Flash

FAQ

Common questions about DeepSeek R1 Distill Qwen 14B vs MiMo-V2-Flash.

Which is better, DeepSeek R1 Distill Qwen 14B or MiMo-V2-Flash?

MiMo-V2-Flash significantly outperforms across most benchmarks. DeepSeek R1 Distill Qwen 14B is made by DeepSeek and MiMo-V2-Flash is made by Xiaomi. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does DeepSeek R1 Distill Qwen 14B compare to MiMo-V2-Flash in benchmarks?

DeepSeek R1 Distill Qwen 14B scores MATH-500: 93.9%, AIME 2024: 80.0%, GPQA: 59.1%, LiveCodeBench: 53.1%. MiMo-V2-Flash scores AIME 2025: 94.1%, Arena-Hard v2: 86.2%, MMLU-Pro: 84.9%, HMMT 2025: 84.4%, GPQA: 83.7%.

What are the context window sizes for DeepSeek R1 Distill Qwen 14B and MiMo-V2-Flash?

DeepSeek R1 Distill Qwen 14B 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.

Who makes DeepSeek R1 Distill Qwen 14B and MiMo-V2-Flash?

DeepSeek R1 Distill Qwen 14B is developed by DeepSeek and MiMo-V2-Flash is developed by Xiaomi.