DeepSeek-V4-Pro-0813 vs QwQ-32B-Preview
Comparing DeepSeek-V4-Pro-0813 and QwQ-32B-Preview across benchmarks, pricing, and capabilities.
DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
DeepSeek-V4-Pro-0813 and QwQ-32B-Preview trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, QwQ-32B-Preview is roughly 3.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V4-Pro-0813 also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Based on current benchmark, pricing, and model metadata for 2026.
Choose DeepSeek-V4-Pro-0813
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Aug 2026
Choose QwQ-32B-Preview
- cost matters — it's about 3.3x cheaper per token
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V4-Pro-0813 and QwQ-32B-Previewdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Pro-0813 ($0.43/1M tokens) is 2.9x more expensive than QwQ-32B-Preview ($0.15/1M tokens).
For output processing, DeepSeek-V4-Pro-0813 ($0.87/1M tokens) is 4.3x more expensive than QwQ-32B-Preview ($0.20/1M tokens).
In conclusion, DeepSeek-V4-Pro-0813 is more expensive than QwQ-32B-Preview.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V4-Pro-0813 has 1567.5B more parameters than QwQ-32B-Preview, making it 4823.1% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V4-Pro-0813 accepts 1,048,576 input tokens compared to QwQ-32B-Preview's 32,768 tokens. DeepSeek-V4-Pro-0813 can generate longer responses up to 393,216 tokens, while QwQ-32B-Preview is limited to 32,768 tokens.
License
Usage and distribution terms
DeepSeek-V4-Pro-0813 is licensed under MIT, while QwQ-32B-Preview uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
DeepSeek-V4-Pro-0813 was released on 2026-08-13, while QwQ-32B-Preview was released on 2024-11-28.
DeepSeek-V4-Pro-0813 is 21 months newer than QwQ-32B-Preview.
Aug 13, 2026
1 weeks ago
1.7yr newerNov 28, 2024
1.7 years ago
Knowledge Cutoff
When training data ends
QwQ-32B-Preview has a documented knowledge cutoff of 2024-11-28, while DeepSeek-V4-Pro-0813's cutoff date is not specified.
We can confirm QwQ-32B-Preview's training data extends to 2024-11-28, but cannot make a direct comparison without DeepSeek-V4-Pro-0813's cutoff date.
—
Nov 2024
Provider Availability
DeepSeek-V4-Pro-0813 is available from DeepSeek, DeepInfra, Novita, Together. QwQ-32B-Preview is available from DeepInfra, Hyperbolic, Fireworks, Together.
DeepSeek-V4-Pro-0813
QwQ-32B-Preview
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Pro-0813 and QwQ-32B-Preview side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Pro-0813 vs QwQ-32B-Preview.