Model Comparison

DeepSeek-R1-0528 vs Qwen3 32B

DeepSeek-R1-0528 shows notably better performance in the majority of benchmarks. Qwen3 32B is 6.1x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

DeepSeek-R1-0528 outperforms in 3 benchmarks (AIME 2024, AIME 2025, LiveCodeBench), while Qwen3 32B is better at 1 benchmark (CodeForces).

DeepSeek-R1-0528 shows notably better performance in the majority of benchmarks.

Mon Apr 13 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Qwen3 32B costs less

For input processing, DeepSeek-R1-0528 ($0.50/1M tokens) is 5.0x more expensive than Qwen3 32B ($0.10/1M tokens).

For output processing, DeepSeek-R1-0528 ($2.15/1M tokens) is 7.2x more expensive than Qwen3 32B ($0.30/1M tokens).

In conclusion, DeepSeek-R1-0528 is more expensive than Qwen3 32B.*

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

Lowest available price from all providers

Mon Apr 13 2026 • llm-stats.com

DeepSeek-R1-0528

Input tokens$0.50

Output tokens$2.15

Best providerDeepinfra

Qwen3 32B

Input tokens$0.10

Output tokens$0.30

Best providerDeepinfra

Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

638.2B diff

DeepSeek-R1-0528 has 638.2B more parameters than Qwen3 32B, making it 1945.7% larger.

DeepSeek-R1-0528

671.0Bparameters

Qwen3 32B

32.8Bparameters

671.0B

DeepSeek-R1-0528

32.8B

Qwen3 32B

Context Window

Maximum input and output token capacity

DeepSeek-R1-0528 accepts 131,072 input tokens compared to Qwen3 32B's 128,000 tokens. DeepSeek-R1-0528 can generate longer responses up to 131,072 tokens, while Qwen3 32B is limited to 128,000 tokens.

DeepSeek-R1-0528

Input131,072 tokens

Output131,072 tokens

Qwen3 32B

Input128,000 tokens

Output128,000 tokens

Mon Apr 13 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-R1-0528 is licensed under MIT, while Qwen3 32B 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

Qwen3 32B

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-R1-0528 was released on 2025-05-28, while Qwen3 32B was released on 2025-04-29.

DeepSeek-R1-0528 is 1 month newer than Qwen3 32B.

DeepSeek-R1-0528

May 28, 2025

10 months ago

4w newer

Qwen3 32B

Apr 29, 2025

11 months 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. Qwen3 32B is available from DeepInfra, Novita, Sambanova.

DeepSeek-R1-0528

Deepinfra

Input Price:Input: $0.50/1MOutput Price:Output: $2.15/1M

DeepSeek

Input Price:Input: $0.55/1MOutput Price:Output: $2.19/1M

Novita

Input Price:Input: $0.70/1MOutput Price:Output: $2.50/1M

Qwen3 32B

Deepinfra

Input Price:Input: $0.10/1MOutput Price:Output: $0.30/1M

Novita

Input Price:Input: $0.10/1MOutput Price:Output: $0.44/1M

Sambanova

Input Price:Input: $0.40/1MOutput Price:Output: $0.80/1M

* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek-R1-0528

View details

DeepSeek

Larger context window (131,072 tokens)

Higher AIME 2024 score (91.4% vs 81.4%)

Higher AIME 2025 score (87.5% vs 72.9%)

Higher LiveCodeBench score (73.3% vs 65.7%)

Qwen3 32B

View details

Alibaba Cloud / Qwen Team

Less expensive input tokens

Less expensive output tokens

Higher CodeForces score (65.9% vs 64.3%)

Detailed Comparison

AI Model Comparison Table
Feature	DeepSeek-R1-0528	Qwen3 32B

FAQ

Common questions about DeepSeek-R1-0528 vs Qwen3 32B

DeepSeek-R1-0528 shows notably better performance in the majority of benchmarks. DeepSeek-R1-0528 is made by DeepSeek and Qwen3 32B 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%. Qwen3 32B scores Arena Hard: 93.8%, AIME 2024: 81.4%, LiveBench: 74.9%, MultiLF: 73.0%, AIME 2025: 72.9%.

Qwen3 32B is 5.0x cheaper for input tokens. DeepSeek-R1-0528 costs $0.50/M input and $2.15/M output via deepinfra. Qwen3 32B costs $0.10/M input and $0.30/M output via deepinfra.

DeepSeek-R1-0528 supports 131K tokens and Qwen3 32B supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

Key differences include context window (131K vs 128K), input pricing ($0.50 vs $0.10/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 Qwen3 32B is developed by Alibaba Cloud / Qwen Team.

DeepSeek-R1-0528 vs Qwen3 32B

Performance Benchmarks

Arena Performance

Pricing Analysis

Model Size

Context Window

License

Release Timeline

Knowledge Cutoff

Provider Availability

DeepSeek-R1-0528

Qwen3 32B

Outputs Comparison

Key Takeaways

DeepSeek-R1-0528

Qwen3 32B

Detailed Comparison

FAQ

Which is better, DeepSeek-R1-0528 or Qwen3 32B?

How does DeepSeek-R1-0528 compare to Qwen3 32B in benchmarks?

Is DeepSeek-R1-0528 cheaper than Qwen3 32B?

What are the context window sizes for DeepSeek-R1-0528 and Qwen3 32B?

What are the main differences between DeepSeek-R1-0528 and Qwen3 32B?

Who makes DeepSeek-R1-0528 and Qwen3 32B?