Model Comparison

DeepSeek-R1-0528 vs Qwen3-235B-A22B-Thinking-2507

Qwen3-235B-A22B-Thinking-2507 significantly outperforms across most benchmarks. DeepSeek-R1-0528 is 1.1x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

5 benchmarks

DeepSeek-R1-0528 outperforms in 1 benchmarks (MMLU-Pro), while Qwen3-235B-A22B-Thinking-2507 is better at 4 benchmarks (AIME 2025, GPQA, Humanity's Last Exam, MMLU-Redux).

Qwen3-235B-A22B-Thinking-2507 significantly outperforms across most benchmarks.

Mon Apr 13 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

DeepSeek-R1-0528 costs less

For input processing, DeepSeek-R1-0528 ($0.50/1M tokens) is 1.7x more expensive than Qwen3-235B-A22B-Thinking-2507 ($0.30/1M tokens).

For output processing, DeepSeek-R1-0528 ($2.15/1M tokens) is 1.4x cheaper than Qwen3-235B-A22B-Thinking-2507 ($3.00/1M tokens).

In conclusion, Qwen3-235B-A22B-Thinking-2507 is more expensive than DeepSeek-R1-0528.*

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

Lowest available price from all providers
Mon Apr 13 2026 • llm-stats.com
DeepSeek
DeepSeek-R1-0528
Input tokens$0.50
Output tokens$2.15
Best providerDeepinfra
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Thinking-2507
Input tokens$0.30
Output tokens$3.00
Best providerFireworks
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

436.0B diff

DeepSeek-R1-0528 has 436.0B more parameters than Qwen3-235B-A22B-Thinking-2507, making it 185.5% larger.

DeepSeek
DeepSeek-R1-0528
671.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Thinking-2507
235.0Bparameters
671.0B
DeepSeek-R1-0528
235.0B
Qwen3-235B-A22B-Thinking-2507

Context Window

Maximum input and output token capacity

Qwen3-235B-A22B-Thinking-2507 accepts 262,144 input tokens compared to DeepSeek-R1-0528's 131,072 tokens. Both models can generate responses up to 131,072 tokens.

DeepSeek
DeepSeek-R1-0528
Input131,072 tokens
Output131,072 tokens
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Thinking-2507
Input262,144 tokens
Output131,072 tokens
Mon Apr 13 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-R1-0528 is licensed under MIT, while Qwen3-235B-A22B-Thinking-2507 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

Qwen3-235B-A22B-Thinking-2507

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-R1-0528 was released on 2025-05-28, while Qwen3-235B-A22B-Thinking-2507 was released on 2025-07-25.

Qwen3-235B-A22B-Thinking-2507 is 2 months newer than DeepSeek-R1-0528.

DeepSeek-R1-0528

May 28, 2025

10 months ago

Qwen3-235B-A22B-Thinking-2507

Jul 25, 2025

8 months ago

1mo 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-R1-0528 is available from DeepInfra, DeepSeek, Novita. Qwen3-235B-A22B-Thinking-2507 is available from Fireworks, Novita.

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

Qwen3-235B-A22B-Thinking-2507

fireworks logo
Fireworks
Input Price:Input: $0.30/1MOutput Price:Output: $3.00/1M
novita logo
Novita
Input Price:Input: $0.30/1MOutput Price:Output: $3.00/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

DeepSeek
Less expensive output tokens
Higher MMLU-Pro score (85.0% vs 84.4%)
Alibaba Cloud / Qwen Team
Larger context window (262,144 tokens)
Less expensive input tokens
Higher AIME 2025 score (92.3% vs 87.5%)
Higher GPQA score (81.1% vs 81.0%)
Higher Humanity's Last Exam score (18.2% vs 17.7%)
Higher MMLU-Redux score (93.8% vs 93.4%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-R1-0528
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Thinking-2507

FAQ

Common questions about DeepSeek-R1-0528 vs Qwen3-235B-A22B-Thinking-2507

Qwen3-235B-A22B-Thinking-2507 significantly outperforms across most benchmarks. DeepSeek-R1-0528 is made by DeepSeek and Qwen3-235B-A22B-Thinking-2507 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%. Qwen3-235B-A22B-Thinking-2507 scores MMLU-Redux: 93.8%, AIME 2025: 92.3%, WritingBench: 88.3%, IFEval: 87.8%, Creative Writing v3: 86.1%.
Qwen3-235B-A22B-Thinking-2507 is 1.7x cheaper for input tokens. DeepSeek-R1-0528 costs $0.50/M input and $2.15/M output via deepinfra. Qwen3-235B-A22B-Thinking-2507 costs $0.30/M input and $3.00/M output via fireworks.
DeepSeek-R1-0528 supports 131K tokens and Qwen3-235B-A22B-Thinking-2507 supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (131K vs 262K), 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 Qwen3-235B-A22B-Thinking-2507 is developed by Alibaba Cloud / Qwen Team.