Model Comparison

DeepSeek-V3 vs QwQ-32B

QwQ-32B significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

5 benchmarks

DeepSeek-V3 outperforms in 1 benchmarks (IFEval), while QwQ-32B is better at 4 benchmarks (AIME 2024, GPQA, LiveCodeBench, MATH-500).

QwQ-32B significantly outperforms across most benchmarks.

Thu Apr 30 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 30 2026 • llm-stats.com
DeepSeek
DeepSeek-V3
Input tokens$0.27
Output tokens$1.10
Best providerDeepSeek
Alibaba Cloud / Qwen Team
QwQ-32B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

638.5B diff

DeepSeek-V3 has 638.5B more parameters than QwQ-32B, making it 1964.6% larger.

DeepSeek
DeepSeek-V3
671.0Bparameters
Alibaba Cloud / Qwen Team
QwQ-32B
32.5Bparameters
671.0B
DeepSeek-V3
32.5B
QwQ-32B

Context Window

Maximum input and output token capacity

Only DeepSeek-V3 specifies input context (131,072 tokens). Only DeepSeek-V3 specifies output context (131,072 tokens).

DeepSeek
DeepSeek-V3
Input131,072 tokens
Output131,072 tokens
Alibaba Cloud / Qwen Team
QwQ-32B
Input- tokens
Output- tokens
Thu Apr 30 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3 is licensed under MIT + Model License (Commercial use allowed), while QwQ-32B uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

DeepSeek-V3

MIT + Model License (Commercial use allowed)

Open weights

QwQ-32B

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V3 was released on 2024-12-25, while QwQ-32B was released on 2025-03-05.

QwQ-32B is 2 months newer than DeepSeek-V3.

DeepSeek-V3

Dec 25, 2024

1.3 years ago

QwQ-32B

Mar 5, 2025

1.2 years ago

2mo newer

Knowledge Cutoff

When training data ends

QwQ-32B has a documented knowledge cutoff of 2024-11-28, while DeepSeek-V3's cutoff date is not specified.

We can confirm QwQ-32B's training data extends to 2024-11-28, but cannot make a direct comparison without DeepSeek-V3's cutoff date.

DeepSeek-V3

—

QwQ-32B

Nov 2024

Outputs Comparison

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Key Takeaways

DeepSeek
Larger context window (131,072 tokens)
Higher IFEval score (86.1% vs 83.9%)
Alibaba Cloud / Qwen Team

QwQ-32B

View details

Alibaba Cloud / Qwen Team

Higher AIME 2024 score (79.5% vs 39.2%)
Higher GPQA score (65.2% vs 59.1%)
Higher LiveCodeBench score (63.4% vs 37.6%)
Higher MATH-500 score (90.6% vs 90.2%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3
Alibaba Cloud / Qwen Team
QwQ-32B

FAQ

Common questions about DeepSeek-V3 vs QwQ-32B

QwQ-32B significantly outperforms across most benchmarks. DeepSeek-V3 is made by DeepSeek and QwQ-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-V3 scores DROP: 91.6%, CLUEWSC: 90.9%, MATH-500: 90.2%, MMLU-Redux: 89.1%, MMLU: 88.5%. QwQ-32B scores MATH-500: 90.6%, IFEval: 83.9%, AIME 2024: 79.5%, LiveBench: 73.1%, BFCL: 66.4%.
DeepSeek-V3 supports 131K tokens and QwQ-32B supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include licensing (MIT + Model License (Commercial use allowed) vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V3 is developed by DeepSeek and QwQ-32B is developed by Alibaba Cloud / Qwen Team.