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Model Comparison

Comprehensive side-by-side analysis of model capabilities and performance

DeepSeek

DeepSeek-V3.1

DeepSeek

DeepSeek-V3.1 is a language model developed by DeepSeek. The model shows competitive results across 16 benchmarks. It excels particularly in SimpleQA (93.4%), MMLU-Redux (91.8%), MMLU-Pro (83.7%). The model shows particular specialization in factuality tasks with an average performance of 92.6%. It supports a 328K token context window for handling large documents. The model is available through 2 API providers. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents DeepSeek's latest advancement in AI technology.

Alibaba Cloud / Qwen Team

QwQ-32B-Preview

Alibaba Cloud / Qwen Team

QwQ-32B-Preview is a language model developed by Alibaba Cloud / Qwen Team. It achieves strong performance with an average score of 64.0% across 4 benchmarks. It excels particularly in MATH-500 (90.6%), GPQA (65.2%), AIME 2024 (50.0%). The model is available through 4 API providers. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Alibaba Cloud / Qwen Team's latest advancement in AI technology.

Alibaba Cloud / Qwen Team

QwQ-32B-Preview

Alibaba Cloud / Qwen Team

2024-11-28

DeepSeek

DeepSeek-V3.1

DeepSeek

2025-01-10

1 month newer

Pricing Comparison

Cost per million tokens (USD)

DeepSeek

DeepSeek-V3.1

Input:$0.27
Output:$1.00
Alibaba Cloud / Qwen Team

QwQ-32B-Preview

$0.92 cheaper
Input:$0.15
Output:$0.20

Performance Metrics

Context window and performance specifications

DeepSeek

DeepSeek-V3.1

Larger context
Max Context:327.7K
Parameters:671.0B
Alibaba Cloud / Qwen Team

QwQ-32B-Preview

Max Context:65.5K
Parameters:32.5B

Average performance across 2 common benchmarks

DeepSeek

DeepSeek-V3.1

+11.3%
Average Score:61.3%
Alibaba Cloud / Qwen Team

QwQ-32B-Preview

Average Score:50.0%

Performance comparison across key benchmark categories

DeepSeek

DeepSeek-V3.1

math
41.6%
general
57.3%
code
+6.5%
56.5%
Alibaba Cloud / Qwen Team

QwQ-32B-Preview

math
+49.0%
90.6%
general
+0.3%
57.6%
code
50.0%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

QwQ-32B-Preview

2024-11-28

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

DeepSeek

DeepSeek-V3.1

2 providers

DeepInfra

Novita

Alibaba Cloud / Qwen Team

QwQ-32B-Preview

4 providers

Together

Throughput: 62.14 tok/s
Latency: 0.74ms

Hyperbolic

Throughput: 31.9 tok/s
Latency: 1.05ms

DeepInfra

Throughput: 76.04 tok/s
Latency: 0.44ms

Fireworks

Throughput: 99.15 tok/s
Latency: 0.53ms
DeepSeek

DeepSeek-V3.1

+11.3%
Avg Score:61.3%
Providers:2
Alibaba Cloud / Qwen Team

QwQ-32B-Preview

Avg Score:50.0%
Providers:4