Model Comparison

DeepSeek R1 Zero vs DeepSeek-R1-0528

DeepSeek-R1-0528 significantly outperforms across most benchmarks.

Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

DeepSeek R1 Zero outperforms in 0 benchmarks, while DeepSeek-R1-0528 is better at 3 benchmarks (AIME 2024, GPQA, LiveCodeBench).

DeepSeek-R1-0528 significantly outperforms across most benchmarks.

Thu Apr 16 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
Thu Apr 16 2026 • llm-stats.com
DeepSeek
DeepSeek R1 Zero
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
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 Zero, making it 0.0% larger.

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

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 Zero
Input- tokens
Output- tokens
DeepSeek
DeepSeek-R1-0528
Input131,072 tokens
Output131,072 tokens
Thu Apr 16 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 Zero

MIT

Open weights

DeepSeek-R1-0528

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Zero 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 Zero.

DeepSeek R1 Zero

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

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Key Takeaways

Larger context window (131,072 tokens)
Higher AIME 2024 score (91.4% vs 86.7%)
Higher GPQA score (81.0% vs 73.3%)
Higher LiveCodeBench score (73.3% vs 50.0%)

Detailed Comparison

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

FAQ

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

DeepSeek-R1-0528 significantly outperforms across most benchmarks. DeepSeek R1 Zero is made by DeepSeek and DeepSeek-R1-0528 is made by DeepSeek. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
DeepSeek R1 Zero scores MATH-500: 95.9%, AIME 2024: 86.7%, GPQA: 73.3%, LiveCodeBench: 50.0%. 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 Zero supports an unknown number of tokens and DeepSeek-R1-0528 supports 131K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.