Model Comparison

DeepSeek-V3.1 vs Qwen3 32B

Qwen3 32B shows notably better performance in the majority of benchmarks. Qwen3 32B is 3.0x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

DeepSeek-V3.1 outperforms in 1 benchmarks (CodeForces), while Qwen3 32B is better at 3 benchmarks (AIME 2024, AIME 2025, LiveCodeBench).

Qwen3 32B shows notably better performance in the majority of benchmarks.

Thu Apr 30 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Qwen3 32B costs less

For input processing, DeepSeek-V3.1 ($0.27/1M tokens) is 2.7x more expensive than Qwen3 32B ($0.10/1M tokens).

For output processing, DeepSeek-V3.1 ($1.00/1M tokens) is 3.3x more expensive than Qwen3 32B ($0.30/1M tokens).

In conclusion, DeepSeek-V3.1 is more expensive than Qwen3 32B.*

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

Lowest available price from all providers
Thu Apr 30 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.1
Input tokens$0.27
Output tokens$1.00
Best providerDeepinfra
Alibaba Cloud / Qwen Team
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-V3.1 has 638.2B more parameters than Qwen3 32B, making it 1945.7% larger.

DeepSeek
DeepSeek-V3.1
671.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3 32B
32.8Bparameters
671.0B
DeepSeek-V3.1
32.8B
Qwen3 32B

Context Window

Maximum input and output token capacity

DeepSeek-V3.1 accepts 163,840 input tokens compared to Qwen3 32B's 128,000 tokens. DeepSeek-V3.1 can generate longer responses up to 163,840 tokens, while Qwen3 32B is limited to 128,000 tokens.

DeepSeek
DeepSeek-V3.1
Input163,840 tokens
Output163,840 tokens
Alibaba Cloud / Qwen Team
Qwen3 32B
Input128,000 tokens
Output128,000 tokens
Thu Apr 30 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3.1 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-V3.1

MIT

Open weights

Qwen3 32B

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.1 was released on 2025-01-10, while Qwen3 32B was released on 2025-04-29.

Qwen3 32B is 4 months newer than DeepSeek-V3.1.

DeepSeek-V3.1

Jan 10, 2025

1.3 years ago

Qwen3 32B

Apr 29, 2025

1.0 years ago

3mo 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-V3.1 is available from DeepInfra, Novita. Qwen3 32B is available from DeepInfra, Novita, Sambanova.

DeepSeek-V3.1

deepinfra logo
Deepinfra
Input Price:Input: $0.27/1MOutput Price:Output: $1.00/1M
novita logo
Novita
Input Price:Input: $0.27/1MOutput Price:Output: $1.00/1M

Qwen3 32B

deepinfra logo
Deepinfra
Input Price:Input: $0.10/1MOutput Price:Output: $0.30/1M
novita logo
Novita
Input Price:Input: $0.10/1MOutput Price:Output: $0.44/1M
sambanova logo
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
Larger context window (163,840 tokens)
Higher CodeForces score (69.7% vs 65.9%)
Alibaba Cloud / Qwen Team

Qwen3 32B

View details

Alibaba Cloud / Qwen Team

Less expensive input tokens
Less expensive output tokens
Higher AIME 2024 score (81.4% vs 66.3%)
Higher AIME 2025 score (72.9% vs 49.8%)
Higher LiveCodeBench score (65.7% vs 56.4%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.1
Alibaba Cloud / Qwen Team
Qwen3 32B

FAQ

Common questions about DeepSeek-V3.1 vs Qwen3 32B

Qwen3 32B shows notably better performance in the majority of benchmarks. DeepSeek-V3.1 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-V3.1 scores SimpleQA: 93.4%, MMLU-Redux: 91.8%, MMLU-Pro: 83.7%, GPQA: 74.9%, CodeForces: 69.7%. Qwen3 32B scores Arena Hard: 93.8%, AIME 2024: 81.4%, LiveBench: 74.9%, MultiLF: 73.0%, AIME 2025: 72.9%.
Qwen3 32B is 2.7x cheaper for input tokens. DeepSeek-V3.1 costs $0.27/M input and $1.00/M output via deepinfra. Qwen3 32B costs $0.10/M input and $0.30/M output via deepinfra.
DeepSeek-V3.1 supports 164K 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 (164K vs 128K), input pricing ($0.27 vs $0.10/M), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V3.1 is developed by DeepSeek and Qwen3 32B is developed by Alibaba Cloud / Qwen Team.