GPT-6 Luna vs QwQ-32B-Preview
GPT-6 Luna leads the LLM Stats Score 44.5 to 9.0. QwQ-32B-Preview is 1.2x cheaper per token.
OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
GPT-6 Luna leads the overall LLM Stats Score 44.5 to 9.0, ranking #41 overall.
On price, QwQ-32B-Preview is roughly 1.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-6 Luna also accepts a larger context window (1,050,000 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-6 Luna
- overall performance matters — it scores 44.5 and ranks #41 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you process long inputs — it offers a 1,050,000 token context window
- you want the most recent training data — it shipped Sep 2026
Choose QwQ-32B-Preview
- cost matters — it's about 1.2x cheaper per token
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Individual benchmarks
5 reported for GPT-6 Luna · 4 for QwQ-32B-Preview
GPT-6 Luna and QwQ-32B-Previewdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-6 Luna ($0.10/1M tokens) is 1.5x cheaper than QwQ-32B-Preview ($0.15/1M tokens).
For output processing, GPT-6 Luna ($0.50/1M tokens) is 2.5x more expensive than QwQ-32B-Preview ($0.20/1M tokens).
In conclusion, GPT-6 Luna 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-6 Luna accepts 1,050,000 input tokens compared to QwQ-32B-Preview's 32,768 tokens. GPT-6 Luna can generate longer responses up to 128,000 tokens, while QwQ-32B-Preview is limited to 32,768 tokens.
Input capabilities
Documented input modalities across available providers
GPT-6 Luna supports multimodal inputs, whereas QwQ-32B-Preview does not.
GPT-6 Luna can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-6 Luna
QwQ-32B-Preview
License
Usage and distribution terms
GPT-6 Luna 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-6 Luna was released on 2026-09-22, while QwQ-32B-Preview was released on 2024-11-28.
GPT-6 Luna is 22 months newer than QwQ-32B-Preview.
Sep 22, 2026
0 days ago
1.8yr newerNov 28, 2024
1.8 years ago
Knowledge Cutoff
When training data ends
GPT-6 Luna has a knowledge cutoff of 2026-05-18, while QwQ-32B-Preview has a cutoff of 2024-11-28.
GPT-6 Luna has more recent training data (up to 2026-05-18), making it potentially better informed about events through that date compared to QwQ-32B-Preview (2024-11-28).
May 2026
1.5 yr newerNov 2024
Provider Availability
GPT-6 Luna is available from OpenAI. QwQ-32B-Preview is available from DeepInfra, Hyperbolic, Fireworks, Together.
GPT-6 Luna
QwQ-32B-Preview
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-6 Luna and QwQ-32B-Preview side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-6 Luna vs QwQ-32B-Preview.