Model Comparison

DeepSeek-R1-0528 vs Qwen2.5 14B InstructWhich is better in 2026?

DeepSeek-R1-0528 significantly outperforms across most benchmarks.

Verdict: DeepSeek-R1-0528 vs Qwen2.5 14B Instruct — which is better?

DeepSeek-R1-0528 (by DeepSeek) and Qwen2.5 14B Instruct (by Alibaba Cloud / Qwen Team) 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-R1-0528 outperforms in 3 benchmarks (GPQA, MMLU-Pro, MMLU-Redux), while Qwen2.5 14B Instruct is better at 0 benchmarks. DeepSeek-R1-0528 significantly outperforms across most benchmarks.

Choose DeepSeek-R1-0528 if…

  • you want the strongest raw capability — it leads on 3 of 3 shared benchmarks
  • you want the most recent training data — it shipped May 2025

Choose Qwen2.5 14B Instruct if…

  • you are already invested in the Alibaba Cloud / Qwen Team ecosystem

Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

DeepSeek-R1-0528 outperforms in 3 benchmarks (GPQA, MMLU-Pro, MMLU-Redux), while Qwen2.5 14B Instruct is better at 0 benchmarks.

DeepSeek-R1-0528 significantly outperforms across most benchmarks.

Wed Jun 24 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

656.3B diff

DeepSeek-R1-0528 has 656.3B more parameters than Qwen2.5 14B Instruct, making it 4464.6% larger.

DeepSeek
DeepSeek-R1-0528
671.0Bparameters
Alibaba Cloud / Qwen Team
Qwen2.5 14B Instruct
14.7Bparameters
671.0B
DeepSeek-R1-0528
14.7B
Qwen2.5 14B Instruct

Context Window

Maximum input and output token capacity

Only DeepSeek-R1-0528 specifies input context (131,072 tokens). Only DeepSeek-R1-0528 specifies output context (131,072 tokens).

DeepSeek
DeepSeek-R1-0528
Input131,072 tokens
Output131,072 tokens
Alibaba Cloud / Qwen Team
Qwen2.5 14B Instruct
Input- tokens
Output- tokens
Wed Jun 24 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-R1-0528 is licensed under MIT, while Qwen2.5 14B Instruct uses Apache 2.0.

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

DeepSeek-R1-0528

MIT

Open weights

Qwen2.5 14B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-R1-0528 was released on 2025-05-28, while Qwen2.5 14B Instruct was released on 2024-09-19.

DeepSeek-R1-0528 is 8 months newer than Qwen2.5 14B Instruct.

DeepSeek-R1-0528

May 28, 2025

1.1 years ago

8mo newer
Qwen2.5 14B Instruct

Sep 19, 2024

1.8 years ago

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

Larger context window (131,072 tokens)
Higher GPQA score (81.0% vs 45.5%)
Higher MMLU-Pro score (85.0% vs 63.7%)
Higher MMLU-Redux score (93.4% vs 80.0%)
Alibaba Cloud / Qwen Team

Qwen2.5 14B Instruct

View details

Alibaba Cloud / Qwen Team

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

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-R1-0528
Alibaba Cloud / Qwen Team
Qwen2.5 14B Instruct

FAQ

Common questions about DeepSeek-R1-0528 vs Qwen2.5 14B Instruct.

Which is better, DeepSeek-R1-0528 or Qwen2.5 14B Instruct?

DeepSeek-R1-0528 significantly outperforms across most benchmarks. DeepSeek-R1-0528 is made by DeepSeek and Qwen2.5 14B Instruct is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does DeepSeek-R1-0528 compare to Qwen2.5 14B Instruct in benchmarks?

DeepSeek-R1-0528 scores MMLU-Redux: 93.4%, SimpleQA: 92.3%, AIME 2024: 91.4%, AIME 2025: 87.5%, MMLU-Pro: 85.0%. Qwen2.5 14B Instruct scores GSM8k: 94.8%, HumanEval: 83.5%, MBPP: 82.0%, MATH: 80.0%, MMLU-Redux: 80.0%.

What are the context window sizes for DeepSeek-R1-0528 and Qwen2.5 14B Instruct?

DeepSeek-R1-0528 supports 131K tokens and Qwen2.5 14B Instruct supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek-R1-0528 and Qwen2.5 14B Instruct?

Key differences include licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-R1-0528 and Qwen2.5 14B Instruct?

DeepSeek-R1-0528 is developed by DeepSeek and Qwen2.5 14B Instruct is developed by Alibaba Cloud / Qwen Team.