Model Comparison

DeepSeek-R1 vs DeepSeek-R1-0528

Comparing DeepSeek-R1 and DeepSeek-R1-0528 across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-R1 and DeepSeek-R1-0528 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

DeepSeek-R1-0528 costs less

For input processing, DeepSeek-R1 ($0.55/1M tokens) is 1.1x more expensive than DeepSeek-R1-0528 ($0.50/1M tokens).

For output processing, DeepSeek-R1 ($2.19/1M tokens) is 1.0x more expensive than DeepSeek-R1-0528 ($2.15/1M tokens).

In conclusion, DeepSeek-R1 is more expensive than DeepSeek-R1-0528.*

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

Lowest available price from all providers
Sat Apr 11 2026 • llm-stats.com
DeepSeek
DeepSeek-R1
Input tokens$0.55
Output tokens$2.19
Best providerDeepSeek
DeepSeek
DeepSeek-R1-0528
Input tokens$0.50
Output tokens$2.15
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

0.0M diff

DeepSeek-R1-0528 has 0.0B more parameters than DeepSeek-R1, making it 0.0% larger.

DeepSeek
DeepSeek-R1
671.0Bparameters
DeepSeek
DeepSeek-R1-0528
671.0Bparameters
671.0B
DeepSeek-R1
671.0B
DeepSeek-R1-0528

Context Window

Maximum input and output token capacity

Both models have the same input context window of 131,072 tokens. Both models can generate responses up to 131,072 tokens.

DeepSeek
DeepSeek-R1
Input131,072 tokens
Output131,072 tokens
DeepSeek
DeepSeek-R1-0528
Input131,072 tokens
Output131,072 tokens
Sat Apr 11 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

MIT

Open weights

DeepSeek-R1-0528

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek-R1 was released on 2025-01-20, while DeepSeek-R1-0528 was released on 2025-05-28.

DeepSeek-R1-0528 is 4 months newer than DeepSeek-R1.

DeepSeek-R1

Jan 20, 2025

1.2 years ago

DeepSeek-R1-0528

May 28, 2025

10 months ago

4mo 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

Provider Availability

DeepSeek-R1 is available from DeepSeek, DeepInfra, Together, Fireworks. DeepSeek-R1-0528 is available from DeepInfra, DeepSeek, Novita.

DeepSeek-R1

deepseek logo
DeepSeek
Input Price:Input: $0.55/1MOutput Price:Output: $2.19/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.85/1MOutput Price:Output: $2.50/1M
together logo
Together
Input Price:Input: $7.00/1MOutput Price:Output: $7.00/1M
fireworks logo
Fireworks
Input Price:Input: $8.00/1MOutput Price:Output: $8.00/1M

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
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

DeepSeek
DeepSeek
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-R1
DeepSeek
DeepSeek-R1-0528

FAQ

Common questions about DeepSeek-R1 vs DeepSeek-R1-0528

DeepSeek-R1 (DeepSeek) and DeepSeek-R1-0528 (DeepSeek) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
DeepSeek-R1-0528 scores MMLU-Redux: 93.4%, SimpleQA: 92.3%, AIME 2024: 91.4%, AIME 2025: 87.5%, MMLU-Pro: 85.0%.
DeepSeek-R1-0528 is 1.1x cheaper for input tokens. DeepSeek-R1 costs $0.55/M input and $2.19/M output via deepseek. DeepSeek-R1-0528 costs $0.50/M input and $2.15/M output via deepinfra.
DeepSeek-R1 supports 131K tokens and DeepSeek-R1-0528 supports 131K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include input pricing ($0.55 vs $0.50/M). See the full comparison above for benchmark-by-benchmark results.