Model Comparison

DeepSeek-R1-0528 vs Qwen2.5 7B Instruct

DeepSeek-R1-0528 significantly outperforms across most benchmarks. Qwen2.5 7B Instruct is 3.0x cheaper per token.

Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

DeepSeek-R1-0528 outperforms in 4 benchmarks (GPQA, LiveCodeBench, MMLU-Pro, MMLU-Redux), while Qwen2.5 7B Instruct is better at 0 benchmarks.

DeepSeek-R1-0528 significantly outperforms across most benchmarks.

Fri Apr 17 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Qwen2.5 7B Instruct costs less

For input processing, DeepSeek-R1-0528 ($0.50/1M tokens) is 1.7x more expensive than Qwen2.5 7B Instruct ($0.30/1M tokens).

For output processing, DeepSeek-R1-0528 ($2.15/1M tokens) is 7.2x more expensive than Qwen2.5 7B Instruct ($0.30/1M tokens).

In conclusion, DeepSeek-R1-0528 is more expensive than Qwen2.5 7B Instruct.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Fri Apr 17 2026 • llm-stats.com
DeepSeek
DeepSeek-R1-0528
Input tokens$0.50
Output tokens$2.15
Best providerDeepinfra
Alibaba Cloud / Qwen Team
Qwen2.5 7B Instruct
Input tokens$0.30
Output tokens$0.30
Best providerTogether
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Model Size

Parameter count comparison

663.4B diff

DeepSeek-R1-0528 has 663.4B more parameters than Qwen2.5 7B Instruct, making it 8717.3% larger.

DeepSeek
DeepSeek-R1-0528
671.0Bparameters
Alibaba Cloud / Qwen Team
Qwen2.5 7B Instruct
7.6Bparameters
671.0B
DeepSeek-R1-0528
7.6B
Qwen2.5 7B Instruct

Context Window

Maximum input and output token capacity

Both models have the same input context window of 131,072 tokens. DeepSeek-R1-0528 can generate longer responses up to 131,072 tokens, while Qwen2.5 7B Instruct is limited to 8,192 tokens.

DeepSeek
DeepSeek-R1-0528
Input131,072 tokens
Output131,072 tokens
Alibaba Cloud / Qwen Team
Qwen2.5 7B Instruct
Input131,072 tokens
Output8,192 tokens
Fri Apr 17 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-R1-0528 is licensed under MIT, while Qwen2.5 7B 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 7B 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 7B Instruct was released on 2024-09-19.

DeepSeek-R1-0528 is 8 months newer than Qwen2.5 7B Instruct.

DeepSeek-R1-0528

May 28, 2025

10 months ago

8mo newer
Qwen2.5 7B Instruct

Sep 19, 2024

1.6 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

Provider Availability

DeepSeek-R1-0528 is available from DeepInfra, DeepSeek, Novita. Qwen2.5 7B Instruct is available from Together.

DeepSeek-R1-0528

deepinfra logo
Deepinfra
Input Price:Input: $0.50/1MOutput Price:Output: $2.15/1M
deepseek logo
DeepSeek
Input Price:Input: $0.55/1MOutput Price:Output: $2.19/1M
novita logo
Novita
Input Price:Input: $0.70/1MOutput Price:Output: $2.50/1M

Qwen2.5 7B Instruct

together logo
Together
Input Price:Input: $0.30/1MOutput Price:Output: $0.30/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Higher GPQA score (81.0% vs 36.4%)
Higher LiveCodeBench score (73.3% vs 28.7%)
Higher MMLU-Pro score (85.0% vs 56.3%)
Higher MMLU-Redux score (93.4% vs 75.4%)
Alibaba Cloud / Qwen Team

Qwen2.5 7B Instruct

View details

Alibaba Cloud / Qwen Team

Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-R1-0528
Alibaba Cloud / Qwen Team
Qwen2.5 7B Instruct

FAQ

Common questions about DeepSeek-R1-0528 vs Qwen2.5 7B Instruct

DeepSeek-R1-0528 significantly outperforms across most benchmarks. DeepSeek-R1-0528 is made by DeepSeek and Qwen2.5 7B Instruct is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
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 7B Instruct scores GSM8k: 91.6%, MT-Bench: 87.5%, HumanEval: 84.8%, MBPP: 79.2%, MATH: 75.5%.
Qwen2.5 7B Instruct is 1.7x cheaper for input tokens. DeepSeek-R1-0528 costs $0.50/M input and $2.15/M output via deepinfra. Qwen2.5 7B Instruct costs $0.30/M input and $0.30/M output via together.
DeepSeek-R1-0528 supports 131K tokens and Qwen2.5 7B Instruct supports 131K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include input pricing ($0.50 vs $0.30/M), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-R1-0528 is developed by DeepSeek and Qwen2.5 7B Instruct is developed by Alibaba Cloud / Qwen Team.