GPT-6 Luna vs Qwen3-Coder
Comparing GPT-6 Luna and Qwen3-Coder across benchmarks, pricing, and capabilities.
OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
GPT-6 Luna and Qwen3-Coder trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, Qwen3-Coder is roughly 1.1x 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
- 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 Qwen3-Coder
- cost matters — it's about 1.1x 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 · 0 for Qwen3-Coder
GPT-6 Luna and Qwen3-Coderdon'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 1.8x cheaper than Qwen3-Coder ($0.18/1M tokens).
For output processing, GPT-6 Luna ($0.50/1M tokens) is 2.8x more expensive than Qwen3-Coder ($0.18/1M tokens).
In conclusion, GPT-6 Luna is more expensive than Qwen3-Coder.*
* 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 Qwen3-Coder's 256,000 tokens. Qwen3-Coder can generate longer responses up to 256,000 tokens, while GPT-6 Luna is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
GPT-6 Luna supports multimodal inputs, whereas Qwen3-Coder 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
Qwen3-Coder
License
Usage and distribution terms
GPT-6 Luna is licensed under a proprietary license, while Qwen3-Coder 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 Qwen3-Coder was released on 2025-01-01.
GPT-6 Luna is 21 months newer than Qwen3-Coder.
Sep 22, 2026
0 days ago
1.7yr newerJan 1, 2025
1.7 years ago
Knowledge Cutoff
When training data ends
GPT-6 Luna has a documented knowledge cutoff of 2026-05-18, while Qwen3-Coder's cutoff date is not specified.
We can confirm GPT-6 Luna's training data extends to 2026-05-18, but cannot make a direct comparison without Qwen3-Coder's cutoff date.
May 2026
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Provider Availability
GPT-6 Luna is available from OpenAI. Qwen3-Coder is available from DeepInfra, Fireworks.
GPT-6 Luna
Qwen3-Coder
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-6 Luna and Qwen3-Coder side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-6 Luna vs Qwen3-Coder.