Model Comparison

DeepSeek R1 Distill Qwen 7B vs DeepSeek-R1-0528Which is better in 2026?

DeepSeek-R1-0528 significantly outperforms across most benchmarks.

Verdict: DeepSeek R1 Distill Qwen 7B vs DeepSeek-R1-0528 — which is better?

DeepSeek R1 Distill Qwen 7B (by DeepSeek) and DeepSeek-R1-0528 (by DeepSeek) 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 7B 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.

Choose DeepSeek R1 Distill Qwen 7B if…

  • you are already invested in the DeepSeek ecosystem

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
Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

DeepSeek R1 Distill Qwen 7B 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.

Sat Jun 13 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

663.4B diff

DeepSeek-R1-0528 has 663.4B more parameters than DeepSeek R1 Distill Qwen 7B, making it 8705.8% larger.

DeepSeek
DeepSeek R1 Distill Qwen 7B
7.6Bparameters
DeepSeek
DeepSeek-R1-0528
671.0Bparameters
7.6B
DeepSeek R1 Distill Qwen 7B
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 Distill Qwen 7B
Input- tokens
Output- tokens
DeepSeek
DeepSeek-R1-0528
Input131,072 tokens
Output131,072 tokens
Sat Jun 13 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 7B

MIT

Open weights

DeepSeek-R1-0528

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Distill Qwen 7B 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 Distill Qwen 7B.

DeepSeek R1 Distill Qwen 7B

Jan 20, 2025

1.4 years ago

DeepSeek-R1-0528

May 28, 2025

1.0 years 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

DeepSeek

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

DeepSeek
Larger context window (131,072 tokens)
Higher AIME 2024 score (91.4% vs 83.3%)
Higher GPQA score (81.0% vs 49.1%)
Higher LiveCodeBench score (73.3% vs 37.6%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek R1 Distill Qwen 7B
DeepSeek
DeepSeek-R1-0528

FAQ

Common questions about DeepSeek R1 Distill Qwen 7B vs DeepSeek-R1-0528.

Which is better, DeepSeek R1 Distill Qwen 7B or DeepSeek-R1-0528?

DeepSeek-R1-0528 significantly outperforms across most benchmarks. DeepSeek R1 Distill Qwen 7B 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.

How does DeepSeek R1 Distill Qwen 7B compare to DeepSeek-R1-0528 in benchmarks?

DeepSeek R1 Distill Qwen 7B scores MATH-500: 92.8%, AIME 2024: 83.3%, GPQA: 49.1%, LiveCodeBench: 37.6%. DeepSeek-R1-0528 scores MMLU-Redux: 93.4%, SimpleQA: 92.3%, AIME 2024: 91.4%, AIME 2025: 87.5%, MMLU-Pro: 85.0%.

What are the context window sizes for DeepSeek R1 Distill Qwen 7B and DeepSeek-R1-0528?

DeepSeek R1 Distill Qwen 7B 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.

Related comparisons