GPT-4o vs QwQ-32B-Preview
GPT-4o and QwQ-32B-Preview are closely matched at 14.2 and 9.1 on the LLM Stats Score. QwQ-32B-Preview is 26.9x cheaper per token.
OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
GPT-4o and QwQ-32B-Preview are closely matched on the overall LLM Stats Score at 14.2 and 9.1.
The models split the 2 individual benchmarks reported for both models evenly.
On price, QwQ-32B-Preview is roughly 26.9x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-4o also accepts a larger context window (128,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GPT-4o
- you process long inputs — it offers a 128,000 token context window
Choose QwQ-32B-Preview
- cost matters — it's about 26.9x cheaper per token
- you want the most recent training data — it shipped Nov 2024
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
38 reported for GPT-4o · 4 for QwQ-32B-Preview
GPT-4o outperforms in 1 benchmarks (GPQA), while QwQ-32B-Preview is better at 1 benchmark (AIME 2024).
Both models are evenly matched across the benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-4o ($2.50/1M tokens) is 16.7x more expensive than QwQ-32B-Preview ($0.15/1M tokens).
For output processing, GPT-4o ($10.00/1M tokens) is 50.0x more expensive than QwQ-32B-Preview ($0.20/1M tokens).
In conclusion, GPT-4o is more expensive than QwQ-32B-Preview.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-4o accepts 128,000 input tokens compared to QwQ-32B-Preview's 32,768 tokens. QwQ-32B-Preview can generate longer responses up to 32,768 tokens, while GPT-4o is limited to 16,384 tokens.
Input capabilities
Documented input modalities across available providers
GPT-4o supports multimodal inputs, whereas QwQ-32B-Preview does not.
GPT-4o can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-4o
QwQ-32B-Preview
License
Usage and distribution terms
GPT-4o is licensed under a proprietary license, while QwQ-32B-Preview uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Apache 2.0
Open weights
Release Timeline
When each model was launched
GPT-4o was released on 2024-08-06, while QwQ-32B-Preview was released on 2024-11-28.
QwQ-32B-Preview is 4 months newer than GPT-4o.
Aug 6, 2024
2.1 years ago
Nov 28, 2024
1.8 years ago
3mo newerKnowledge Cutoff
When training data ends
QwQ-32B-Preview has a documented knowledge cutoff of 2024-11-28, while GPT-4o'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 GPT-4o's cutoff date.
—
Nov 2024
Provider Availability
GPT-4o is available from Azure, OpenAI. QwQ-32B-Preview is available from DeepInfra, Hyperbolic, Fireworks, Together.
GPT-4o
QwQ-32B-Preview
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-4o and QwQ-32B-Preview side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-4o vs QwQ-32B-Preview.