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.

Want to compare interactively?Try the playground

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.

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-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
Mon Apr 13 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
Mon Apr 13 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

11 months 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.